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  • 1.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    An efficient algorithm for the pseudo likelihood estimation of the generalized linear mixed models (GLMM) with correlated random effects2009Report (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with correlated random effects. The proposed estimation technique does not require reparametarisation of the model. Multivariate Taylor's approximation has been used to approximate the intractable integrals in the likelihood function of the GLMM. Based on the analytical expression for the estimator of the covariance matrix of the random effects, a condition has been presented as to when such a covariance matrix can be estimated through the estimates of the random effects. An application of the model with a binary response variable has been presented using a real data set on credit defaults from two Swedish banks. Due to the use of two-step estimation technique, proposed algorithm outperforms the conventional pseudo likelihood algorithms in terms of computational time.

  • 2.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Feasible computation of the generalized linear mixed models with application to credit risk modelling2010Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis deals with developing and testing feasible computational procedures to facilitate the estimation of and carry out the prediction with the generalized linear mixed model (GLMM) with a scope of applying them to large data sets. The work of this thesis is motivated from an issue arising in credit risk modelling. We have access to a huge data set, consisting of about one million observations, on credit history obtained from two major Swedish banks. The principal research interest involved with the data analysis is to model the probability of credit defaults by incorporating the systematic dependencies among the default events. In order to model the dependent credit defaults we adopt the framework of GLMM which is a popular approach to model correlated binary data. However, existing computational procedures for GLMM did not offer us the flexibility to incorporate the desired correlation structure of defaults events. For the feasible estimation of the GLMM we propose two estimation techniques being the fixed effects (FE) approach and the two-step pseudo likelihood approach (2PL). The preciseness of the estimation techniques and their computational advantages are studied by Monte-Carlo simulations and by applying them to the credit risk modelling. Regarding the prediction issue, we show how to apply the likelihood principle to carry out prediction with GLMM. We also provide an R add-in package to facilitate the predictive inference for GLMM.

  • 3.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups2010Manuscript (preprint) (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

  • 4.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Industry shocks and empirical evidences on defaults comovement2009Report (Other academic)
    Abstract [en]

    It is commonly agreed that the credit defaults are correlated. However, the mechanism of such dependence is not yet fully understood. This paper contributes to the current understanding about the defaults comovement in the following way. Assuming that the industries provides the basis of defaults comovement it provides empirical evidence as to how such comovements can be modeled using correlated industry shocks. Generalized linear mixed model (GLMM) with correlated random effects is used to model the defaults comovement. Empirical evidences are drawn through analyzing individual borrower level credit history data obtained from two major Swedish banks between the period 1994-2000. The results show that the defaults are correlated both within and between industries but not over time (quarters). A discussion has also been presented as to how a GLMM for defaults correlation can be explained.

  • 5.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Likelihood prediction for generalized linear mixed models under covariate uncertainty2014In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 2, 219-234 p.Article in journal (Refereed)
    Abstract [en]

    This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

  • 6.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Computionally feasible estimation of the covariance structure in generalized linear mixed models2008In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 78, no 12, 1229-1239 p.Article in journal (Refereed)
    Abstract [en]

    In this paper, we discuss how a regression model, with a non-continuous response variable, which allows for dependency between observations, should be estimated when observations are clustered and measurements on the subjects are repeated. The cluster sizes are assumed to be large. We find that the conventional estimation technique suggested by the literature on generalized linear mixed models (GLMM) is slow and sometimes fails due to non-convergence and lack of memory on standard PCs. We suggest to estimate the random effects as fixed effects by generalized linear model and to derive the covariance matrix from these estimates. A simulation study shows that our proposal is feasible in terms of mean-square error and computation time. We recommend that our proposal be implemented in the software of GLMM techniques so that the estimation procedure can switch between the conventional technique and our proposal, depending on the size of the clusters.

  • 7.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Chen, Rui
    Liang, Yuli
    How to determine the progression of young skiers?2008In: CHANCE: New Directions for Statistics and Computing, ISSN 0933-2480, Vol. 21, no 4, 13-19 p.Article in journal (Refereed)
  • 8.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Linde, Olof
    Sweco Eurofutures.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandén, Peter
    Sweco Eurofutures.
    Wing, Stefan
    Sweco Eurofutures.
    Utvärdering av det arbetsmarknadspolitiska projektet "Volvo Cars och dess underleverantörer"2012Report (Other academic)
    Abstract [sv]

    Denna rapport är en utvärdering av det arbetsmarknadspolitiska projektet "Volvo Cars och dess underleverantörer", som har genomförts av Arbetsförmedlingen i samarbete med Skolverket och Svenska ESF-rådet. Den 5 juni 2009 ansökte Sveriges regering om medel hos den Europeiska globaliseringsfonen (EGF)2 för att kunna erbjuda åtgärder för personer som blivit uppsagda från Volvo Cars AB och dess underleverantörer. Syftet med projektet var att kunna erbjuda de som blivit uppsagda kompetensutveckling, nya yrkeskunskaper och möjlighet att etablera egna företag.

    På operativ nivå drevs projektet i samverkan mellan Arbetsförmedlingen och den kom-munala yrkesvuxenutbildningen ("Yrkesvux"). Yrkesvux i Göteborgs kommun fick i upp-drag av Skolverket att samordna den del av verksamheten som berörde kommunal yr-kesvuxenutbildning. Projektet startade 1 januari 2010 och avslutades 31 maj 2011. Enligt kommissionens beslut fick medel även användas retroaktivt för insatser som hade givits till de uppsagda i form av olika arbetsmarknadsutbildningar, det s.k. snabbspåret, under 2009 innan projektet hade startat.

    Av nästan 5 000 individer i målgruppen som registrerade sig vid Arbetsförmedlingen del-tog knappt en fjärdedel i projektets insatser (exkl. vägledning). Av dessa gick 55 procent i aktiviteter enbart genom Arbetsförmedlingen, 37 procent enbart genom Yrkesvux och åtta procent genom både Arbetsförmedlingen och Yrkesvux. De vanligaste förekommande utbildningsinriktningarna var industri och bygg, fordonsindustri, transport och magasine-ring, omvårdnad och handel.

  • 9.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Hao, Chengcheng
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Review of the literature on credit risk modeling: development of the past 10 years2010In: Banks and Bank Systems, ISSN 1816-7403, Vol. 5, no 3, 43-60 p.Article in journal (Refereed)
    Abstract [en]

    This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.

  • 10.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Maengseok, Noh
    Department of Statistics, Pukyong National University, South Korea.
    Lee, Youngjo
    Department of Statistics, Seoul National University, South Korea.
    Likelihood estimate of treatment effects under selection bias2013In: Statistics and its Interface, ISSN 1938-7989, E-ISSN 1938-7997, Vol. 6, no 3, 349-359 p.Article in journal (Refereed)
    Abstract [en]

    We consider methods for estimating the causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, a simple comparison of treated and control outcomes will not generally yield valid estimates of casual effect. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based on some strong assumptions, which are not directly testable. In this paper, we present an alternative modelling approach to draw causal inferences by using a shared random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but also is less sensitive to model misspecifications, which we consider, than existing methods.

  • 11.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Department of Statistics, Pukyong National Univeristy.
    Lee, Youngjo
    Department of Statistics, Seoul National Univeristy.
    Likelihood estimate of treatment effects under selection bias2012Report (Other academic)
    Abstract [en]

    We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

  • 12.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Karolinska Institutet.
    Fitting conditional and simultaneous autoregressive spatial models in hglm2015In: The R Journal, ISSN 2073-4859, Vol. 7, no 2, 5-18 p.Article in journal (Refereed)
    Abstract [en]

    We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

  • 13.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Swedish University of Agricultural Sciences, Uppsala.
    Fitting spatial models in the R package: hglm2014Report (Other academic)
    Abstract [en]

    We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

  • 14. Besnier, Francois
    et al.
    Wahlberg, Per
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Ek, Weronika
    Andersson, Leif
    Siegel, Paul
    Carlborg, Örjan
    Fine mapping and replication of QTL in outbred chicken advanced intercross lines2011In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 43, 3Article in journal (Refereed)
    Abstract [en]

    Background: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

    Methods: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

    Results: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

    Conclusions: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

  • 15.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    A comment on outlier detection and skewed distributions2017Report (Other academic)
    Abstract [en]

    It seems that a paper of mine appearing in Computational Statistics & Data Analysis (Carling, 2000) has prompted the development of outlier detection methods for highly skewed data. However, I wrote the paper in the spirit of Exploratory Data Analysis (Tukey, 1977) and I shared Tukey’s opinion, and I still hold it, that skewed data are better to be transformed for approximate symmetry prior to detection of outliers (or other data analyses).

  • 16.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    GRASP and statistical bounds for heuristic solutions to combinatorial problems2016Report (Other academic)
    Abstract [en]

    The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few metaheuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds has previously been found reliable when obtained from the Genetic algorithm whereas in this work they found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.

  • 17.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Li, Yujiao
    Dalarna University, School of Technology and Business Studies, Statistics.
    The Power of the Synthetic Control Method2016Report (Other academic)
    Abstract [en]

    The synthetic control method (SCM) is a new, popular method developed for the purpose of estimating the effect of an intervention when only one single unit has been exposed. Other similar, unexposed units are combined into a synthetic control unit intended to mimic the evolution in the exposed unit, had it not been subject to exposure. As the inference relies on only a single observational unit, the statistical inferential issue is a challenge. In this paper, we examine the statistical properties of the estimator, study a number of features potentially yielding uncertainty in the estimator, discuss the rationale for statistical inference in relation to SCM, and provide a Web-app for researchers to aid in their decision of whether SCM is powerful for a specific case study. We conclude that SCM is powerful with a limited number of controls in the donor pool and a fairly short pre-intervention time period. This holds as long as the parameter of interest is a parametric specification of the intervention effect, and the duration of post-intervention period is reasonably long, and the fit of the synthetic control unit to the exposed unit in the pre-intervention period is good.

  • 18.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Confidence in heuristic solutions?2015In: Journal of Global Optimization, ISSN 0925-5001, E-ISSN 1573-2916, Vol. 63, no 2, 381-399 p.Article in journal (Refereed)
    Abstract [en]

    Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test p-median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.

  • 19.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Confidence in heuristic solutions?2014Report (Other academic)
    Abstract [en]

    Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test p-median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.

  • 20.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    On statistical bounds of heuristic solutions to location problems2016In: Journal of combinatorial optimization, ISSN 1382-6905, E-ISSN 1573-2886, Vol. 31, no 4, 1518-1549 p.Article in journal (Refereed)
    Abstract [en]

    Solutions to combinatorial optimization problems, such as problems of locating facilities, frequently rely on heuristics to minimize the objective function. The optimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. Pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small, almost dormant, branch of the literature suggests using statistical principles to estimate the minimum and its bounds as a tool to decide upon stopping and evaluating the quality of the solution. In this paper we examine the functioning of statistical bounds obtained from four different estimators by using simulated annealing on p-median test problems taken from Beasley’s OR-library. We find the Weibull estimator and the 2nd order Jackknife estimator preferable and the requirement of sample size to be about 10 being much less than the current recommendation. However, reliable statistical bounds are found to depend critically on a sample of heuristic solutions of high quality and we give a simple statistic useful for checking the quality. We end the paper with an illustration on using statistical bounds in a problem of locating some 70 distribution centers of the Swedish Post in one Swedish region.

  • 21.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    On statistical bounds of heuristic solutions to location problems2014Report (Other academic)
    Abstract [en]

    Solutions to combinatorial optimization problems, such as problems of locating facilities, frequently rely on heuristics to minimize the objective function. The optimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. Pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small, almost dormant, branch of the literature suggests using statistical principles to estimate the minimum and its bounds as a tool to decide upon stopping and evaluating the quality of the solution. In this paper we examine the functioning of statistical bounds obtained from four different estimators by using simulated annealing on p-median test problems taken from Beasley’s OR-library. We find the Weibull estimator and the 2nd order Jackknife estimator preferable and the requirement of sample size to be about 10 being much less than the current recommendation. However, reliable statistical bounds are found to depend critically on a sample of heuristic solutions of high quality and we give a simple statistic useful for checking the quality. We end the paper with an illustration on using statistical bounds in a problem of locating some 70 distribution centers of the Swedish Post in one Swedish region. 

  • 22. Casals, M.
    et al.
    Langohr, K.
    Carrasco, J. L.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study2015In: SORT - Statistics and Operations Research Transactions, ISSN 1696-2281, E-ISSN 2013-8830, Vol. 39, no 2, 281-308 p.Article in journal (Refereed)
    Abstract [en]

    Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

  • 23.
    Felleki, Majbritt
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences.
    Genetic Heteroscedasticity for Domestic Animal Traits2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean.

    The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows.

    The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased.

    For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

  • 24.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Chalkias, Helena
    A Double Hierarchical Generalized Linear Model For Teat Number In Pigs2010Conference paper (Other academic)
  • 25.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lee, Dongwhan
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Lee, Youngjo
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Gilmour, Arthur R.
    School of Mathematics and Applied Statistics, Faculty of Informatics, University of Wollongong, Wollongong, NSW 2522, Australia.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models2012In: Genetics Research, ISSN 0016-6723, Vol. 94, no 6, 307-317 p.Article in journal (Refereed)
    Abstract [en]

    The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being −0·52 for IRWLS and −0·62 in Sorensen & Waagepetersen (2003).

  • 26.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Sveriges Lantbruksuniversitet.
    Lundeheim, Nils
    Sveriges Lantbruksuniversitet.
    Genetic Control of Residual Variance for Teat Number in Pigs2013In: Proc. Assoc. Advmt. Anim. Breed. Genet., AAABG , 2013, 538-541 p.Conference paper (Other academic)
    Abstract [en]

    The genetic improvement in litter size in pigs has been substantial during the last 10-15 years. The number of teats on the sow must increase as well to meet the needs of the piglets, because each piglet needs access to its own teat. We applied a genetic heterogeneity model on teat numberin sows, and estimated medium-high heritability for teat number (0.5), but low heritability for residual variance (0.05), indicating that selection for reduced variance might have very limited effect. A numerically positive correlation (0.8) between additive genetic breeding values for mean and for variance was found, but because of the low heritability for residual variance, the variance will increase very slowly with the mean.

  • 27.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundeheim, Nils
    Sveriges lantbruksuniversitet, Institutionen för husdjursgenetik.
    Genetic Heteroscedasticity for Teat Count in PigsManuscript (preprint) (Other academic)
  • 28.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundeheim, Nils
    SLU.
    Genetic heteroscedasticity of teat count in pigs2015In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 132, no 5, 392-398 p.Article in journal (Refereed)
    Abstract [en]

    The genetic improvement in pig litter size has been substantial. The number of teats on the sowmust thus increase as well to meet the needs of the piglets, because each piglet needs access to itsown teat. We applied a genetic heterogeneity model to teat counts in pigs, and estimated a mediumheritability for teat counts (0.35), but found a low heritability for residual variance (0.06),indicating that selection for reduced residual variance might have a limited effect. A numericallypositive correlation (0.8) was estimated between the breeding values for the mean and the residualvariance. However, because of the low heritability of the residual variance, the residual variance will probably increase very slowly with the mean.

  • 29.
    Han, Mengjie
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Humanities and Media Studies, Cultural Studies.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    How do different densities in a network affect the optimal location of service centers?2013Report (Other academic)
    Abstract [en]

    The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

  • 30.
    Han, Mengjie
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    How does the use of different road networks effect the optimal location of facilities in rural areas?2012Report (Other academic)
    Abstract [en]

    The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure.

    Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia.

    The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

  • 31.
    Han, Mengjie
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    How do neighbouring populations affect local population change over time?2013Report (Other academic)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse how local population changes are affected by neighbouring populations. To do so we use the last 200 years of local population change that redistributed population in Sweden. We use literature to identify several different processes and spatial dependencies in the redistribution between a parish and its surrounding parishes. The analysis is based on a unique unchanged historical parish division, and we use an index of local spatial correlation to describe different kinds of spatial dependencies that have influenced the redistribution of the population. To control inherent time dependencies, we introduce a non-separable spatial temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies can be observed simultaneously over time. The main conclusions are that while local population changes have been highly dependent on the neighbouring populations in the 19th century, this spatial dependence have become insignificant already when two parishes is separated by 5 kilometres in the late 20th century. Another conclusion is that the time dependency in the population change is higher when the population redistribution is weak, as it currently is and as it was during the 19th century until the start of industrial revolution.

  • 32.
    Han, Mengjie
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. HUI Research.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography. HUI Research, Stockholm.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. HUI Research, Stockholm.
    To what extent do neighbouring populations affect local population growth over time?2016In: Population, Space and Place, ISSN 1544-8444, E-ISSN 1544-8452, Vol. 22, no 1, 68-83 p.Article in journal (Refereed)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse to what extent local population change is affected by neighbouring populations. To do this, we focused on the last 190 years of local population change that redistributed population in Sweden. We used literature to identify several different processes in the population redistribution. The different processes implied different spatial dependencies between local population change and the surrounding populations. The analysis is based on an unchanged historical parish division, and we used an index of local spatial correlation to describe different types of spatial dependencies that influenced the redistribution of the population. To control inherent time dependencies, we introduced a non-separable spatial-temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies could be simultaneously observed over time. The main conclusions are that while local population changes have been highly dependent on neighbouring populations in the 19th century, this spatial dependence became insignificant already when two parishes are separated by 5 km in the late 20th century. It is argued that the only process that significantly redistributed the population at the end of the 20th century is the immigration to Sweden.

  • 33.
    He, Changli
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandberg, Rickard
    Testing parameter constancy in unit root autoregressive models against multiple continuous structural changes2012In: Econometric Reviews, ISSN 0747-4938, E-ISSN 1532-4168, Vol. 31, no 1, 34-59 p.Article in journal (Refereed)
    Abstract [en]

    This article considers tests for logistic smooth transition autoregressive (LSTAR) models accommodating multiple time dependent transitions between regimes when the data generating process is a random walk. The asymptotic null distributions of the tests, in contrast to the standard results in Lin and Teräsvirta (1994), are nonstandard. Monte Carlo experiments reveal that the tests have modest size distortions and satisfactory power against LSTAR models with multiple smooth breaks. The tests are applied to Swedish unemployment rates and the hysteresis hypothesis is over-turned in favour of an LSTAR model with two transitions between extreme regimes.

  • 34.
    He, Changli
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Teräsvirta, Timo
    An extended constant conditional correlation GARCH model and its fourth-moment structure2004In: Econometric Theory, ISSN 0266-4666, E-ISSN 1469-4360, Vol. 20, no 5, 904-926 p.Article in journal (Refereed)
    Abstract [en]

    The constant conditional correlation general autoregressive conditional heteroskedasticity (GARCH) model is among the most commonly applied multivariate GARCH models and serves as a benchmark against which other models can be compared. In this paper we consider an extension to this model and examine its fourth-moment structure. The extension, first defined by Jeantheau (1998, Econometric Theory 14, 70–86), is motivated by the result found and discussed in this paper that the squared observations from the extended model have a rich autocorrelation structure. This means that already the first-order model is capable of reproducing a whole variety of autocorrelation structures observed in financial return series. These autocorrelations are derived for the first- and the second-order constant conditional correlation GARCH model. The usefulness of the theoretical results of the paper is demonstrated by reconsidering an empirical example that appeared in the original paper on the constant conditional correlation GARCH model.

  • 35.
    He, Changli
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Teräsvirta, Timo
    Properties of moments of a family of GARCH processes1999In: Journal of Econometrics, ISSN 0304-4076, E-ISSN 1872-6895, Vol. 92, no 1, 173-192 p.Article in journal (Refereed)
    Abstract [en]

    This paper considers the moments of a family of first-order GARCH processes. First, a general condition for the existence of any integer moment of the absolute values of the observations is given. Second, a general expression for this moment as a function of lower-order moments is derived. Third, the kurtosis and the autocorrelation function of the squared and absolute-valued observations are derived. The results apply to a number of different GARCH parameterizations. Finally, the existence, or lack thereof, of the theoretical counterpart to the so-called Taylor effect in some members of this GARCH family is discussed. Possibilities of extending the results to higher-order GARCH processes are indicated and potential applications of the statistical theory proposed.

  • 36.
    He, Changli
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Teräsvirta, Timo
    Gónzalez, Andrés
    Testing parameter constancy in stationary vector autoregressive models against continuous change2008In: Econometric Reviews, ISSN 0747-4938, E-ISSN 1532-4168, Vol. 28, no 1-3, 225-245 p.Article in journal (Refereed)
    Abstract [en]

    In this article we derive a parameter constancy test of a stationary vector autoregressive model against the hypothesis that the parameters of the model change smoothly over time. A single structural break is contained in this alternative hypothesis as a special case. The test is a generalization of a single-equation test of a similar hypothesis proposed in the literature. An advantage here is that the asymptotic distribution theory is standard. The performance of the tests is compared to that of generalized Chow-tests and found satisfactory in terms of both size and power.

  • 37.
    Jia, Tao
    et al.
    Högskolan i Gävle.
    Jiang, Bin
    Högskolan i Gävle.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bohlin, Magnus
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Ban, Yifang
    KTH.
    An empirical study on human mobility and its agent-based modeling2012In: Journal of Statistical Mechanics: Theory and Experiment, ISSN 1742-5468, P11024Article in journal (Refereed)
    Abstract [en]

    This paper aims to analyze the GPS traces of 258 volunteers for a better understanding of both the human mobility patterns and the mechanism. We report the regular and scaling properties of human mobility from several aspects, and importantly we find its levy flight characteristic which is consistent with the previous studies. We further assume two factors that may govern the levy flight property: (1) the scaling and hierarchical properties of the purpose clusters which serve as the underlying spatial structure, and (2) the individual preferential behavior. To verify the assumptions, we implement an agent-based model with the two factors, and the simulated agents indeed reproduce the same levy flight pattern as the observed one. In order to enable the model to reproduce more mobility patterns, we add the model a third factor, the jumping factor which means the probability that one person may cancel the regular mobility schedule and visit a random place. With this factor, our model could cover a relatively wide range of human mobility patterns with exponent values from 1.55 to 2.05.

  • 38. Lee, Youngjo
    et al.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, M
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Skarin, Anna
    Analyzing spatially correlated counts with excessive zeros: a case of modeling the changes of reindeer distribution2013Report (Other academic)
  • 39. Lee, Youngjo
    et al.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Data Analysis Using Hierarchical Generalized Linear Models with R2017Book (Other academic)
  • 40.
    Li, Dao
    Dalarna University, School of Technology and Business Studies, Statistics. Handelshögskolan vid Örebro universitet, Statistik.
    Common Features in Vector Nonlinear Time Series Models2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area.

    Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified.

    The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

  • 41.
    Li, Dao
    Dalarna University, School of Technology and Business Studies, Statistics.
    Residual-based Inference for Common Nonlinear Features2013Report (Other academic)
    Abstract [en]

    This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

  • 42.
    Li, Dao
    Dalarna University, School of Technology and Business Studies, Statistics.
    Testing linear cointegration against smooth-transition cointegration2011Report (Other academic)
    Abstract [en]

    This paper studies a smooth-transition (ST) type cointegration. The proposed ST cointegration allows for regime switching structure in a cointegrated system. It nests the linear cointegration developed by Engle and Granger (1987) and the threshold cointegration studied by Balke and Fomby (1997). We develop F-type tests to examine linear cointegration against ST cointegration in ST-type cointegrating regression models with or without time trends. The null asymptotic distributions of the tests are derived with stationary transition variables in ST cointegrating regression models. And it is shown that our tests have nonstandard limiting distributions expressed in terms of standard Brownian motion when regressors are pure random walks, while have standard asymptotic distributions when regressors contain random walks with nonzero drift. Finite-sample distributions of those tests are studied by Monto Carlo simulations. The small-sample performance of the tests states that our F-type tests have a better power when the system contains ST cointegration than when the system is linearly cointegrated. An empirical example for the purchasing power parity (PPP) data (monthly US dollar, Italy lira and dollar-lira exchange rate from 1973:01 to 1989:10) is illustrated by applying the testing procedures in this paper. It is found that there is no linear cointegration in the system, but there exits the ST-type cointegration in the PPP data.

  • 43.
    Li, Dao
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    He, Changli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Forecasting with Vector Nonlinear Time Series Models2013Report (Other academic)
    Abstract [en]

    This work concerns forecasting with vector nonlinear time series models when errorsare correlated. Point forecasts are numerically obtained using bootstrap methods andillustrated by two examples. Evaluation concentrates on studying forecast equality andencompassing. Nonlinear impulse responses are further considered and graphically sum-marized by highest density region. Finally, two macroeconomic data sets are used toillustrate our work. The forecasts from linear or nonlinear model could contribute usefulinformation absent in the forecasts form the other model.

  • 44.
    Li, Dao
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    He, Changli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Testing common nonlinear features in vector nonlinear autoregressive models2012Report (Other academic)
    Abstract [en]

    This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

  • 45.
    Meng, Xiangli
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    He, Changli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach2012Report (Other academic)
    Abstract [en]

    This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

  • 46.
    Mihaescu, Oana
    et al.
    Dalarna University, School of Technology and Business Studies, Human Geography.
    vom Hofe, Rainer
    University of Cincinnati, School of Planning.
    Using Spatial Regression to Estimate Property Tax Discounts from Proximity to Brownfields: A Tool for Local Policy-Making2013In: Journal of Environmental Assessment Policy and Management, ISSN 1464-3332, Vol. 15, no 1Article in journal (Refereed)
    Abstract [en]

    This paper assesses the discount in property values due to proximity to brownfields using a spatial hedonic price model. Using two Bayesian hedonic pricing models, namely the spatial lag of X (SLX) model and the spatial Durbin error model (SDEM), this study identifies a significant decrease in property values for properties located within 2,000 feet of a brownfield. The loss in property value and the subsequent decrease in tax revenue for the City of Cincinnati, Ohio, are then calculated based on these results. Using logarithmic transformations of the property value and the distance to the nearest brownfield variables, we calculate that a 1% increase in the average distance to the closest brownfield leads to a 0.0893% increase in market value. This translates into a $2,262,569 total annual revenue loss for the City of Cincinnati that could presumably be recovered following brownfield cleanup. In addition to accounting for the phenomenon of spatial dependence, this study contributes to the urban planning and environmental policy literature by providing a method for local policy-makers to identify and estimate the negative effects of brownfield sites on local tax revenue.

  • 47. Mischenko, Kateryna
    et al.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Holmgren, Sverker
    Mishchenko, Vladimir
    Assessing a multiple QTL search using the variance component model2010In: Computational biology and chemistry (Print), ISSN 1476-9271, E-ISSN 1476-928X, Vol. 34, no 1, 34-41 p.Article in journal (Refereed)
    Abstract [en]

    Development of variance component algorithms in genetics has previously mainly focused on animal breeding models or problems in human genetics with a simple data structure. We study alternative methods for constrained likelihood maximization in quantitative trait loci (QTL) analysis for large complex pedigrees. We apply a forward selection scheme to include several QTL and interaction effects, as well as polygenic effects, with up to five variance components in the model. We show that the implemented active set and primal-dual schemes result in accurate solutions and that they are robust. In terms of computational speed, a comparison of two approaches for approximating the Hessian of the log-likelihood shows that the method using an average information matrix is the method of choice for the five-dimensional problem. The active set method, with the average information method for Hessian computation, exhibits the fastest convergence with an average of 20 iterations per tested position, where the change in variance components <0.0001 was used as convergence criterion.

  • 48. Nelson, Ronald M
    et al.
    Temnykh, Svetlana V
    Johnson, Jennifer L
    Kharlamova, Anastasiya V
    Vladimirova, Anastasiya V
    Shepeleva, Darya V
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Trut, Lyudmila N
    Carlborg, Örjan
    Kukekova, Anna V
    Genetics of interactive behavior in silver foxes (Vulpes vulpes)2017In: Behavior Genetics, ISSN 0001-8244, E-ISSN 1573-3297, Vol. 47, no 1, 88-101 p.Article in journal (Refereed)
    Abstract [en]

    Individuals involved in a social interaction exhibit different behavioral traits that, in combination, form the individual's behavioral responses. Selectively bred strains of silver foxes (Vulpes vulpes) demonstrate markedly different behaviors in their response to humans. To identify the genetic basis of these behavioral differences we constructed a large F2 population including 537 individuals by cross-breeding tame and aggressive fox strains. 98 fox behavioral traits were recorded during social interaction with a human experimenter in a standard four-step test. Patterns of fox behaviors during the test were evaluated using principal component (PC) analysis. Genetic mapping identified eight unique significant and suggestive QTL. Mapping results for the PC phenotypes from different test steps showed little overlap suggesting that different QTL are involved in regulation of behaviors exhibited in different behavioral contexts. Many individual behavioral traits mapped to the same genomic regions as PC phenotypes. This provides additional information about specific behaviors regulated by these loci. Further, three pairs of epistatic loci were also identified for PC phenotypes suggesting more complex genetic architecture of the behavioral differences between the two strains than what has previously been observed.

  • 49.
    Nelson, Ronald Michael
    et al.
    Swedish University of Agricultural Sciences.
    Nettelblad, Carl
    Uppsala University.
    Pettersson, Mats E
    Swedish University of Agricultural Sciences.
    Shen, Xia
    Swedish University of Agricultural Sciences; Uppsala University;.
    Crooks, Lucy
    Swedish University of Agricultural Sciences.
    Besnier, Francois
    Swedish University of Agricultural Sciences.
    Alvarez-Castro, José
    Swedish University of Agricultural Sciences.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Ek, Weronica
    Swedish University of Agricultural Sciences.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences.
    MAPfastR: quantitative trait loci mapping in outbred line crosses2013In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, Vol. 12, no 3, 2147-2149 p.Article in journal (Refereed)
    Abstract [en]

    MAPfastR is a software package developed to analyze QTL data from inbred and outbred line-crosses. The package includes a number of modules for fast and accurate QTL analyses. It has been developed in the R language for fast and comprehensive analyses of large datasets. MAPfastR is freely available at: http://www.computationalgenetics.se/?page_id=7.

  • 50.
    Nyberg, Roger G.
    et al.
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Gupta, Narendra K.
    Edinburgh Napier University.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Inter-rater reliability in determining the types of vegetation on railway trackbeds2015In: Web Information Systems Engineering – WISE 2015: 16th International Conference, Miami, FL, USA, November 1-3, 2015, Proceedings, Part II / [ed] Wang, J., Cellary, W., Wang, D., Wang, H., Chen, S.-C., Li, T., Zhang, Y., Springer, 2015, Vol. 9419, 379-390 p.Conference paper (Refereed)
    Abstract [en]

    Vegetation growing on railway trackbeds and embankments can present several potential problems. Consequently, such vegetation iscontrolled through various maintenance procedures. In order to investigate the extent of maintenance needed, one of the first steps in anymaintenance procedure is to monitor or inspect the railway section in question. Monitoring is often carried out manually by sending out inspectorsor by watching recorded video clips of the section in question.To facilitate maintenance planning, the ability to assess the extent of vegetation becomes important. This paper investigates the reliability ofhuman assessments of vegetation on railway trackbeds.In this study, five maintenance engineers made independent visual estimates of vegetation cover and counted the number of plant clusters fromimages.The test results showed an inconsistency between the raters when it came to visually estimating plant cover and counting plant clusters. The resultsshowed that caution should be exercised when interpreting individual raters’ assessments of vegetation.

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