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  • 51. Meng, Xiangli
    et al.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    How do administrative borders affect accessibility to hospitals? The case of Sweden2018In: International Journal of Health Planning and Management, ISSN 0749-6753, E-ISSN 1099-1751, Vol. 33, no 3Article in journal (Refereed)
    Abstract [en]

    An administrative border might hinder the optimal allocation of a given set of resources by restricting the flow of goods, services, and people. In this paper, we address the question: Do administrative borders lead to poor accessibility to public service? In answering the question, we have examined the case of Sweden and its regional administrative borders and hospital accessibility. We have used detailed data on the Swedish road network, its hospitals, and its geo-coded population. We have assessed the population's spatial accessibility to Swedish hospitals by computing the inhabitants' distance to the nearest hospital. We have also elaborated several scenarios ranging from strongly confining regional borders to no confinements of borders and recomputed the accessibility. Our findings imply that administrative borders are only marginally worsening the accessibility.

  • 52.
    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.

  • 53.
    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, E-ISSN 1757-5605, 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.

  • 54. 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, p. 34-41Article 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.

  • 55.
    Mouresan, Elena Flavia
    et al.
    Swedish University of Agricultural Sciences.
    Selle, Maria
    Norwegian University of Science and Technology.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Genomic Prediction Including SNP-Specific Variance Predictors2019In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, article id g3.400381.2019Article in journal (Refereed)
    Abstract [en]

    The increasing amount of available biological information on the markers can be used to inform the models applied for genomic selection to improve predictions. The objective of this study was to propose a general model for genomic selection using a link function approach within the hierarchical generalized linear model framework (hglm) that can include external information on the markers. These models can be fitted using the well-established hglm package in R. We also present an R package (CodataGS) to fit these models, which is significantly faster than the hglm package. Simulated data was used to validate the proposed model. We tested categorical, continuous and combination models where the external information on the markers was related to 1) the location of the QTLs on the genome with varying degree of uncertainty, 2) the relationship of the markers with the QTLs calculated as the LD between them, and 3) a combination of both. The proposed models showed improved accuracies from 3.8% up to 23.2% compared to the SNP-BLUP method in a simulated population derived from a base population with 100 individuals. Moreover, the proposed categorical model was tested on a dairy cattle dataset for two traits (Milk Yield and Fat Percentage). These results also showed improved accuracy compared to SNP-BLUP, especially for the Fat% trait. The performance of the proposed models depended on the genetic architecture of the trait, as traits that deviate from the infinitesimal model benefited more from the external information. Also, the gain in accuracy depended on the degree of uncertainty of the external information provided to the model. The usefulness of these type of models is expected to increase with time as more accurate information on the markers becomes available.

  • 56. 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, p. 88-101Article 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.

  • 57.
    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, p. 2147-2149Article 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.

  • 58.
    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, p. 379-390Conference 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.

  • 59.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences.
    The evolution of peer-reviewed papers.2019In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 136, no 2, p. 77-78Article in journal (Other academic)
  • 60.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Al-Sarraj, Razaw
    von Rosen, Dietrich
    Non-iterative variance component estimation in QTL analysis.2009In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 126, no 1, p. 110-116Article in journal (Refereed)
    Abstract [en]

    In variance component quantitative trait loci (QTL) analysis, a mixed model is used to detect the most likely chromosome position of a QTL. The putative QTL is included as a random effect and a method is needed to estimate the QTL variance. The standard estimation method used is an iterative method based on the restricted maximum likelihood (REML). In this paper, we present a novel non-iterative variance component estimation method. This method is based on Henderson's method 3, but relaxes the condition of unbiasedness. Two similar estimators were compared, which were developed from two different partitions of the sum of squares in Henderson's method 3. The approach was compared with REML on data from a European wild boar × domestic pig intercross. A meat quality trait was studied on chromosome 6 where a functional gene was known to be located. Both partitions resulted in estimated QTL variances close to the REML estimates. From the non-iterative estimates, we could also compute good approximations of the likelihood ratio curve on the studied chromosome.

  • 61.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Felleki, Majbritt
    Dalarna University, School of Technology and Business Studies, Statistics.
    Fikse, Freddy
    Mulder, Herman A.
    Strandberg, Erling
    Genetic heterogeneity of residual variance: estimation of variance components using double hierarchical generalized linear models2010In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 42, article id 8Article in journal (Refereed)
    Abstract [en]

    Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms.

    Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model.

    Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

  • 62.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish Univ Agr Sci, Dept Anim Breeding & Genet, S-75007 Uppsala, Sweden.
    Felleki, Majbritt
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish Univ Agr Sci, Dept Anim Breeding & Genet, S-75007 Uppsala, Sweden.
    Fikse, W. F.
    Mulder, H. A.
    Strandberg, E.
    Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle2013In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 96, no 4, p. 2627-2636Article in journal (Refereed)
    Abstract [en]

    Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed.

  • 63.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Lee, Y
    Seoul National University, Seoul, Korea.
    Exploring the potential of hierarchical generalized linear models in animal breeding and genetics2013In: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 130, no 6, p. 415-416Article in journal (Refereed)
  • 64.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lee, Youngjo
    Hierarchical generalized linear models have a great potential in genetics and animal breeding2010Conference paper (Refereed)
  • 65.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    McFarlane, S. Eryn
    Uppsala universitet.
    Husby, Arlid
    University of Helsinki; Norwegian University of Science and Technology.
    Kawakami, Takeshi
    Uppsala universitet.
    Ellegren, Hans
    Uppsala universitet.
    Qvarnström, Anna
    Uppsala universitet.
    Increasing the power of genome wide association studies in natural populations using repeated measures: evaluation and implementation2016In: Methods in Ecology and Evolution, ISSN 2041-210X, E-ISSN 2041-210X, Vol. 7, no 7, p. 792-799Article in journal (Refereed)
    Abstract [en]

    1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful.

    2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden.

    3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response.

    4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

  • 66.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Statistics.
    Vinterkonferens i rumslig statistik i Dalarna2011In: Qvintensen, ISSN 2000-1819, Vol. 2011, no 4Article in journal (Other academic)
  • 67.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Hglm: A package for fitting hierarchical generalized linear models2010In: The R Journal, ISSN 2073-4859, E-ISSN 2073-4859, Vol. 2, no 2, p. 20-28Article in journal (Refereed)
    Abstract [en]

    We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

  • 68.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Valdar, William
    Detecting major genetic loci controlling phenotypic variability in experimental crosses2011In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 188, no 2, p. 435-447Article in journal (Refereed)
    Abstract [en]

    Traditional methods for detecting genes that affect complex diseases in humans or animal models, milk production in livestock, or other traits of interest, have asked whether variation in genotype produces a change in that trait’s average value. But focusing on differences in the mean ignores differences in variability about that mean. The robustness, or uniformity, of an individual’s character is not only of great practical importance in medical genetics and food production but is also of scienti?c and evolutionary interest (e.g., blood pressure in animal models of heart disease, litter size in pigs, ?owering time in plants). We describe a method for detecting major genes controlling the phenotypic variance, referring to these as vQTL. Our method uses a double generalized linear model with linear predictors based on probabilities of line origin. We evaluate our method on simulated F2 and collaborative cross data, and on a real F2 intercross, demonstrating its accuracy and robustness to the presence of ordinary mean-controlling QTL. We also illustrate the connection between vQTL and QTL involved in epistasis, explaining how these concepts overlap. Our method can be applied to a wide range of commonly used experimental crosses and may be extended to genetic association more generally.

  • 69.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease2018Conference paper (Other academic)
    Abstract [en]

    The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

  • 70.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    Novel Statistical Methods in Quantitative Genetics: Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation2012Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models.

    In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision. 

    Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction.

    A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. 

    The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

  • 71. Shen, Xia
    et al.
    Li, Ying
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Uden, Peter
    Carlborg, Orjan
    Application of a genomic model for high-dimensional chemometric analysis2014In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 28, no 7, p. 548-557Article in journal (Refereed)
    Abstract [en]

    The rapid development of newtechnologies for large-scale analysis of genetic variation in the genomes of individuals and populations has presented statistical geneticists with a grand challenge to develop efficient methods for identifying the small proportion of all identified genetic polymorphisms that have effects on traits of interest. To address such a "large p small n" problem, we have developed a heteroscedastic effects model (HEM) that has been shown to be powerful in high-throughput genetic analyses. Here, we describe how this whole-genome model can also be utilized in chemometric analysis. As a proof of concept, we use HEM to predict analyte concentrations in silage using Fourier transform infrared spectroscopy signals. The results show that HEM often outperforms the classic methods and in addition to this presents a substantial computational advantage in the analyses of such high-dimensional data. The results thus show the value of taking an interdisciplinary approach to chemometric analysis and indicate that large-scale genomic models can be a promising new approach for chemometric analysis that deserve to be evaluated more by experts in the field. The software used for our analyses is freely available as an R package at http://cran.r-project.org/web/packages/bigRR/. Copyright (C) 2014 JohnWiley & Sons, Ltd.

  • 72.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty2010Conference paper (Other academic)
    Abstract [en]

    Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

  • 73.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carlborg, Örjan
    Hierarchical likelihood opens a new way of estimating genetic values using genome-wide dense marker maps2011In: BMC Proceedings, ISSN 1753-6561, E-ISSN 1753-6561, Proc. 14th European Workshop on QTL Mapping and Marker Assisted Selection (QTL-MAS), no 5(Suppl 3)Article in journal (Refereed)
    Abstract [en]

    Background Genome-wide dense markers have been used to detect genes and estimate relative genetic values. Among many methods, Bayesian techniques have been widely used and shown to be powerful in genome-wide breeding value estimation and association studies. However, computation is known to be intensive under the Bayesian framework, and specifying a prior distribution for each parameter is always required for Bayesian computation. We propose the use of hierarchical likelihood to solve such problems. Results Using double hierarchical generalized linear models, we analyzed the simulated dataset provided by the QTLMAS 2010 workshop. Marker-specific variances estimated by double hierarchical generalized linear models identified the QTL with large effects for both the quantitative and binary traits. The QTL positions were detected with very high accuracy. For young individuals without phenotypic records, the true and estimated breeding values had Pearson correlation of 0.60 for the quantitative trait and 0.72 for the binary trait, where the quantitative trait had a more complicated genetic architecture involving imprinting and epistatic QTL. Conclusions Hierarchical likelihood enables estimation of marker-specific variances under the likelihoodist framework. Double hierarchical generalized linear models are powerful in localizing major QTL and computationally fast.

  • 74.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carlborg, Örjan
    How to deal with genotype uncertainty in variance component quantitative trait loci analyses2011In: Genetics Research, ISSN 0016-6723, Vol. 93, no 5, p. 333-342Article in journal (Refereed)
    Abstract [en]

    Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

  • 75. Shukur, Ghazi
    et al.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Framtida utmaningar för forskarutbildningen i statistik2013In: Qvintensen, ISSN 2000-1819, no 4, p. 21-21Article in journal (Other (popular science, discussion, etc.))
  • 76.
    Svenson, Kristin
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    A Microdata Analysis Approach to Transport Infrastructure Maintenance2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy.

    This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance.

    Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies.

    In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

  • 77.
    Svenson, Kristin
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimated lifetimes of road pavements in Sweden using time-to-event analysis2014In: Journal of transportation engineering, ISSN 0733-947X, E-ISSN 1943-5436, Vol. 140, no 11, article id 04014056Article in journal (Refereed)
    Abstract [en]

    Maintenance planning of road pavement requires reliable estimates of roads' lifetimes. In determining the lifetime of a road, this study combines maintenance activities and road condition measurements. The scope of the paper is to estimate lifetimes of road pavements in Sweden with time-to-event analysis. The model is stratified according to traffic load and includes effects of pavement type, road type, bearing capacity, road width, speed limit, stone size, and climate zone. Among the nine analyzed pavement types, stone mastic had the longest expected lifetime with a hazard ratio (risk of needing maintenance) estimated to be 36% lower than asphalt concrete. Among road types, 2+1 roads had 22% higher hazard ratio than ordinary roads indicating significantly lower lifetimes. Increased speed lowered the lifetime, while increased stone size (up to 20 mm) and increased road width lengthened the lifetime. The results are of importance for life-cycle cost analysis and road management. (C) 2014 American Society of Civil Engineers.

  • 78.
    Svenson, Kristin
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Li, Yujiao
    Dalarna University, School of Technology and Business Studies, Statistics.
    Macuchova, Zuzana
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Evaluating needs of road maintenance in Sweden with the mixed proportional hazards model2016In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2589, p. 51-58Article in journal (Refereed)
    Abstract [en]

    National road databases often lack important information for long-term maintenance planning of paved roads. In the Swedish case, latent variables of which there are no recordings in the pavement management systems database are, for example, underlying road construction, subsoil conditions, and amount of heavy traffic measured by the equivalent single-axle load. The mixed proportional hazards model with random effects was used to capture the effect of these latent variables on a road's risk of needing maintenance. Estimation of random effects makes it possible to identify sections that have shorter or longer lifetimes than could be expected from the observed explanatory variables (traffic load, pavement type, road type, climate zone, road width, speed limit, and bearing capacity restrictions). The results indicate that the mixed proportional hazards model is useful for maintenance planning because the weakest and strongest sections in a road network can be identified. The effect of the latent variables was visualized by,plotting the random effect of each section in a map of the road network. In addition, the spatial correlation between road sections was evaluated by fitting the random effects in an intrinsic conditional autoregressive model. The spatial correlation was estimated to explain 17% of the variation in lifetimes of roads that occur because of the latent variables. The Swedish example shows that the mixed proportional hazards and intrinsic conditional autoregressive models are suitable for analyzing the effect of latent variables in national road databases.

  • 79.
    Svenson, Kristin
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    McRobbie, S.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Detecting road pavement deterioration with finite mixture models2019In: The international journal of pavement engineering, ISSN 1029-8436, E-ISSN 1477-268X, Vol. 20, no 4, p. 458-465Article in journal (Refereed)
    Abstract [en]

    Budget restrictions often limit the number of possible maintenance activities in a road network each year. To effectively allocate resources, the rate of road pavement deterioration is of great importance. If two maintenance candidates have an equivalent condition, it is reasonable to maintain the segment with the highest deterioration rate first. To identify such segments, finite mixture models were applied to road condition data from a part of the M4 highway in England. Assuming that data originates from two different normal distributions – defined as a ‘change’ distribution and an ‘unchanged’ distribution – all road segments were classified into one of the groups. Comparisons with known measurement errors and maintenance records showed that segments in the unchanged group had a stationary road condition. Segments classified into the change group showed either a rapid deterioration, improvement in condition because of previous maintenance or unusual measurement errors. Together with additional information from maintenance records, finite mixture models can identify segments with the most rapid deterioration rate, and contribute to more efficient maintenance decisions.

  • 80.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, Filip
    Johansson, Dongni
    Memedi, Mevludin
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience2019In: Journal of Neurology, ISSN 0340-5354, E-ISSN 1432-1459, Vol. 266, no 3, p. 651-658Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: Dosing schedules for oral levodopa in advanced stages of Parkinson's disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).

    MATERIALS AND METHODS: In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson's KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments.

    RESULTS: The SBDS maintenance and morning dosing suggestions had a Pearson's correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician's adjustments.

    CONCLUSION: This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

  • 81.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Memedi, Mevludin
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    The effect of continuous levodopa treatment during the afternoon hours2019In: Acta Neurologica Scandinavica, ISSN 0001-6314, E-ISSN 1600-0404, Vol. 139, no 1, p. 70-75Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The aim of this retrospective study was to investigate if patients with PD, who are treated with levodopa-carbidopa intestinal gel (LCIG), clinically worsen during the afternoon hours and if so, to evaluate whether this occurs in all LCIG-treated patients or in a sub-group of patients.

    METHODS: Three published studies were identified and included in the analysis. All studies provided individual response data assessed on the treatment response scale (TRS) and patients were treated with continuous LCIG. Ninety-eight patients from the three studies fulfilled the criteria. T-tests were performed to find differences on the TRS values between the morning and the afternoon hours, linear mixed effect models were fitted on the afternoon hours' evaluations to find trends of wearing-off, and patients were classified into three TRS categories (meaningful increase in TRS, meaningful decrease in TRS, non -meaningful increase or decrease).

    RESULTS: In all three studies significant statistical differences were found between the morning TRS values and the afternoon TRS values (p-value <= 0.001 in all studies). The linear mixed effect models had significant negative coefficients for time in two studies, and 48 out of 98 patients (49%) showed a meaningful decrease of TRS during the afternoon hours.

    CONCLUSION: The results from all studies were consistent, both in the proportion of patients in the three groups and the value of TRS decrease in the afternoon hours. Based on these findings there seems to be a group of patients with predictable "off" behavior in the later parts of the day. This article is protected by copyright. All rights reserved.

  • 82. Wang, Yu
    et al.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Är kommunala sommarjobb en gräddfil till arbetsmarknaden?2006Report (Other academic)
  • 83.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A Note on Proxy Variables and Instrument Variable Regression2015Report (Other academic)
    Abstract [en]

    This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

  • 84.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015Report (Other academic)
  • 85.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015In: Economics Letters, ISSN 0165-1765, E-ISSN 1873-7374, Vol. 137, p. 62-69Article in journal (Refereed)
    Abstract [en]

    About a decade ago William H. Greene introduced the so-called ‘True fixed effects’ (TFE) model, which is intended to discriminate between heterogeneity and efficiency in stochastic frontier analysis. We would say that the TFE model has had a huge impact on applied stochastic frontier analysis. One problem with the original TFE estimator, is its inconsistency in cases with finite time observations, at least for the variance components. For the normal-half-normal model, this problem was solved by Chen et al. (2014) based on maximum likelihood estimation of the within-transformed model. In this study, we illustrate the possibilities offered by method of moments estimation. This approach is more flexible than the MLE proposed by Chen et al. (2014), since the method of moments estimators are not so closely dependent on the distributional assumptions and do not hinge on an explicit distribution of the random error. We only assume symmetry, as well as a fixed fourth-order cumulant for more complicated models. Greene’s methodology can, and has been, generalized to other models than the normal-half-normal model. However, the method of moments estimators proposed here are consistent.

  • 86.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    The true fixed effects model with non-stationary inefficiency distribution2015Report (Other academic)
  • 87.
    Yella, Siril
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyberg, Roger G
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Gupta, Narendra K.
    Edinburgh Napier University.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Reliability of manual assessments in determining the types of vegetation on railway tracks2015In: 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. 9149, p. 391-399Conference paper (Refereed)
    Abstract [en]

    Current day vegetation assessments within railway maintenance are (to a large extent) carried out manually. This study has investigated the reliability of such manual assessments by taking three non-domain experts into account. Thirty-five track images under different conditions were acquired for the purpose. For each image, the raters’ were asked to estimate the cover of woody plants, herbs and grass separately (in %) using methods such as aerial canopy cover, aerial foliar cover and sub-plot frequency. Visual estimates of raters’ were recorded and analysis-of-variance tests on the mean cover estimates were investigated to see whether if there were disagreements between the raters’.  In tra-correl ation coefficient was used to study the differences between the estimates. Results achieved in this work revealed that seven out of the nine analysis-of-variance tests conducted in this study have demonstrated significant difference in the mean estimates of cover (p < 0.05).

  • 88.
    Youngjo, Lee
    et al.
    Seoul National University.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Pukyong National University, Korea.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Skarin, Anna
    Swedish University of Agricultural Science, Uppsala.
    Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts2016In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 6, no 19, p. 7047-7056Article in journal (Refereed)
    Abstract [en]

    We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

  • 89.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of spatio-temporal car movements: a case study2015In: Journal of Location Based Services, ISSN 1748-9725, Vol. 9, no 4, p. 235-253Article in journal (Refereed)
    Abstract [en]

    The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatio-temporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step by step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden. 

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