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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.
    An efficient estimation of the GLMM with correlated random effects2008In: COMPSTAT'2008: International Conference on Computational Statistics / [ed] Moudud, Alam, Porto-Portugal, 2008Conference paper (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for the generalized linear mixed models (GLMM) with random effects being correlated (possibly between subjects). Due to the use of the two-step estimation technique the proposed algorithm outperforms the conventional pseudo likelihood algorithms, e.g. Wolfinger and O’Connell (1993), in terms of computational time. Moreover, it does not require any reparametarisation of the model such as Lindstrom and Bates (1989). 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 estimation technique with a binary response variable is presented using a real data set on credit defaults.

  • 3.
    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.

  • 4.
    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.

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  • 5.
    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.

  • 6.
    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, p. 219-234Article 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.

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  • 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.
    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, p. 1229-1239Article 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.

  • 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.
    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, p. 13-19Article in journal (Refereed)
  • 9.
    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.

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  • 10.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Har kommunala sommarjobb under gymnasieåren en positiv effekt på arbetskarriären senare i livet?2013Report (Other academic)
    Abstract [sv]

    Att erbjuda sommarjobb till ungdomar ses i många länder som ett sätt att förbättra ungdomars möjligheter att komma in och etablera sig på arbetsmarknaden. I Sverige erbjuder de flesta kommuner, delvis finansierat med statliga medel, sommarjobb till ungdomar. Den forskning som finns kring effekten av sommarjobb för ungdomar pekar dock i olika riktningar och lider ofta av metodproblem. Vi undersöker här med bättre metodologiska förutsättningar om kommunala sommarjobb för gymnasieungdomar i Falu kommun har någon positiv effekt på den postgymnasiala inkomstutvecklingen. Vi följer 2 650 ungdomar som, under första året i gymnasiet, ansökte om kommunalt sommarjobb. Vi följer dem tills de når en ålder av som mest 29 år. De kommunala sommarjobben fördelades genom ett lotteriförfarande där alla som ansökte hade lika stor chans att bli tilldelad ett sommarjobb. Vi finner ingen programeffekt för män. För kvinnor upptäcker vi en positiv effekt och då speciellt för kvinnor med låga betyg från grundskolan.

  • 11.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    High-School Students´ Summer Jobs and their Ensuing Labor Market Achievement: the Long Term Effect2013Report (Other academic)
    Abstract [en]

    In part because of high and persistent youth unemployment, adolescent students’ transition from school to work is an important policy and research topic. Many countries have implemented public programs offering summer jobs or work while in high-school as measures to smooth the transition. While the immediate effect of the programs on school attendance, school grades, and disposable income is well documented, their effect on the transition to the labor market remains an open question. Observational studies have shown strong positive effects of summer jobs, but also that the estimated effect is highly vulnerable to selection bias. In this paper, some 3700 high-school students applying for summer jobs in the period 1995-2003,via a program, are followed to 30 years of age. A quarter of the applicants were randomly offered a summer job each year. Among the remaining students, 50% had a (non-program related) summer job while in high-school. We find the income, post high-school, for the offered and non-offered groups to be similar and conclude that the effect of summer jobs on the transition to the labor market is inconsequential.

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  • 12.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sommarjobb, arbetslivserfarenhet och framtida arbetsinkomst2015In: Arbetsmarknad & Arbetsliv, ISSN 1400-9692, Vol. 21, no 4, p. 26-40Article in journal (Refereed)
    Abstract [sv]

    De flesta kommuner erbjuder sommarjobb till gymnasieungdomar. Vi har undersökt om denna arbetslivserfarenhet påverkar flickors framtida arbetsinkomster. Vi följde 1 447 flickor i fem till tolv år efter avslutat gymnasium. Flickorna hade under sitt första gymnasieår ansökt och slumpmässigt tilldelats sommarjobb av Falu kommun. Effekten av sommarjobbserfarenheten var positiv och betydande för dem.

  • 13.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The effect of summer jobs on post-schooling incomes2013Report (Other academic)
    Abstract [en]

    In part because of high youth unemployment, students’ transition from school to work is an important policy and research topic. Public programs offering summer jobs or work while in high school as measures to smooth the transition is commonplace. The immediate effect of the programs on school attendance, school grades, and disposable income is well documented. However, their effect on the transition to the labor market remains unsettled, partly because of a potential selection bias in previous observational studies. In this paper, 2650 first graders of high school in Falun Council, Sweden, randomly allotted summer jobs via a program in the years of 1997-2003, are followed ten years after graduation. The program led to a substantially larger accumulation of work experience while in high school for offered (particularly weak academically performing) females, but not for offered males. Hence, the immediate program effect was heterogeneous. Females were used to estimate the causal effect of work experience while in high school on post-schooling incomes. The (statistically) significant estimate implies an elasticity of 0.4. Work experience while in high school seems to be of future benefit, but the elasticity is potentially inflated due to heterogeneous effects that we were unable to account for.

  • 14.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The program and treatment effect of summer jobs on girls’ post-schooling incomes2014Report (Other academic)
    Abstract [en]

    Public programs (of disputed effect) offering summer jobs or work while in high school to smooth the transition from school to work is commonplace. In this paper, 1447 girls in their first grade of high school between 1997-2003 and randomly allotted summer jobs via a program in Falun (Sweden) are followed 5-12 years after graduation. The program led to a substantially larger accumulation of income while in high school. The causal effect of the high school income on post-schooling incomes was substantial and statistically significant. The implied elasticity of 0.4 is however potentially inflated dueto heterogeneous effects.

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  • 15.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The program and treatment effect of summer jobs on girls’ post-schooling incomes2015In: Evaluation review, ISSN 0193-841X, E-ISSN 1552-3926, Vol. 39, no 3, p. 339-359Article in journal (Refereed)
    Abstract [en]

    Background: Public programs offering summer jobs to smooth the transition from school to work is commonplace. However, the empirical support for summer jobs is limited. This article exploits the availability of registered individual information and random allocation to summer jobs to provide empirical evidence on this issue. 

    Objectives: To identify the effect of summer job programs on the post-schooling incomes of the intended participants. Also to identify the effect of sophomore girls' high school work experience on their post-schooling incomes. 

    Research design: In this article, 1,447 sophomore girls from 1997 to 2003 are followed 5-12 years after graduation. They all applied to Falun municipality's (Sweden) summer job program, and about 25% of them were randomly allotted a job. The random allocation to a summer job is used to identify the causal effect of sophomore girls' high school income on their post-schooling incomes. 

    Subjects: All the 1,447 sophomore girls who applied to Falun municipality's summer job program during 1997-2003. 

    Measures: Annual post-schooling income is used as an outcome measure. The work experience of girls in high school is also measured in terms of total income while in high school. 

    Results: The program led to a substantially larger accumulation of income during high school as well as 19% higher post-schooling incomes. The high school income led to a post-schooling income elasticity of 0.37 which is, however, potentially heterogeneous with regard to academic ability. 

    Conclusions: Both the program effect and the causal effect of high school income on post-schooling incomes were substantial and statistically significant.

  • 16.
    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, p. 43-60Article 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.

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  • 17.
    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, p. 349-359Article 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.

  • 18.
    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.

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  • 19.
    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, p. 5-18Article 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.

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  • 20.
    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).

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  • 21.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Wang, Yu
    When are non-experimental estimates close to experimental estimates?: Evidence from a study of summer job effects in Sweden2007Report (Other academic)
  • 22.
    Karim, Hawzheen
    et al.
    Dalarna University, School of Technology and Business Studies, Road Technology.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Magnusson, Rolf
    Dalarna University, School of Technology and Business Studies, Road Technology.
    Road barrier repair costs and influencing factors2011In: Journal of transportation engineering, ISSN 0733-947X, E-ISSN 1943-5436, Vol. 137, no 5, p. 349-359Article in journal (Refereed)
    Abstract [en]

    This paper presents a study that examines repair costs for different road barrier types and factors that influence these costs. The analyses focused on w-beam and cable barriers used as median barriers. To some extent, pipe barriers, Kohlswa-beam barriers, and concrete barriers were also studied. The influencing factors included in this study were road type, speed limit, barrier type, and seasonal effects. A case study was conducted in four regions of the Swedish Road Administration. Data were collected from 1,625 barrier repairs carried out during 2005 and 2006. The results show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher along collision-free roads than along motorways and 4-lane roads. The results also show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher for cable barrier than for other barrier types. No conclusion can be drawn regarding influence of speed limits on barrier repairs and associated costs as the result from the regions are divergent and not statistically significant. DOI: 10.1061/(ASCE)TE.1943-5436.0000227. (C) 2011 American Society of Civil Engineers.

  • 23. 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)
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    WP_2013
  • 24.
    Lee, Youngjo
    et al.
    Department of Statistics, Seoul National University, Seoul, Republic of Korea.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandström, Per
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå.
    Skarin, Anna
    Department of Animal Nutrition and Management, Swedish University of Agricultural Science, Uppsala.
    Estimating zones of influence using threshold regression2020Report (Other academic)
    Abstract [en]

    In environmental impact assessments, it is important to be able to estimate influence of anthropogenic activities on animal populations. To quantify the influence, it is common to estimate how far, in distance, from a given disturbance source there is an influence on the animals’ habitat selection through estimating a zone of influence (ZOI). Usually, ZOI is estimated for one disturbance source at a time. In this work, we demonstrate how threshold regression modelling can be used for estimating ZOI from several possible sources of disturbances, simultaneously. Based on the theoretical properties of different estimation methods for the estimation of threshold regression we select a set of estimation methods and compare their merits through a simulation study and a real data example. The simulation results revealed that Adaptive Lasso, and Hierarchical likelihood (HL) methods, are two reasonable methods for dealing with the problem. HL performed better than Adaptive Lasso in that it had much higher success rate in identifying correct threshold with small sample size whereas Adaptive Lasso requires large sample to assure good performance. While Adaptive lasso needed to be aided with suitable weights, which are not easy to find, HL method did not require any prior weights. These two methods were applied to estimate the ZOI around 40 wind turbines and surrounding public roads on reindeer habitat selection in winter, by using GPS positioning data from 42 reindeer in north of Sweden in December to March (2012-2015). The results showed that both the disturbance sources have a negative effect on reindeer habitat selection in winter. The HL approach showed that the negative ZOI from the nearest wind turbine was 1.8 km (approx.), however the trend of higher selection of areas further away from the wind turbines was evident up to 4 km (approx.) from the active wind turbines.

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  • 25.
    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.

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  • 26.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.