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Träfflista för sökning "hsv:(NATURVETENSKAP) hsv:(Matematik) hsv:(Sannolikhetsteori och statistik) ;pers:(Rönnegård Lars)"

Sökning: hsv:(NATURVETENSKAP) hsv:(Matematik) hsv:(Sannolikhetsteori och statistik) > Rönnegård Lars

  • Resultat 1-10 av 38
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1.
  • Mischenko, Kateryna, et al. (författare)
  • Assessing a multiple QTL search using the variance component model
  • 2010
  • Ingår i: Computational biology and chemistry (Print). - : Elseiver. - 1476-9271 .- 1476-928X. ; 34:1, s. 34-41
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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2.
  • Alam, Moudud, 1976-, et al. (författare)
  • Fitting conditional and simultaneous autoregressive spatial models in hglm
  • 2015
  • Ingår i: The R Journal. - 2073-4859. ; 7:2, s. 5-18
  • Tidskriftsartikel (refereegranskat)abstract
    • 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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3.
  • Alam, Moudud, et al. (författare)
  • Fitting spatial models in the R package: hglm
  • 2014
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • 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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4.
  • Besnier, Francois, et al. (författare)
  • Fine mapping and replication of QTL in outbred chicken advanced intercross lines
  • 2011
  • Ingår i: Genetics Selection Evolution. - Paris : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 43, s. 3-
  • Tidskriftsartikel (refereegranskat)abstract
    • 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. 
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6.
  • Casals, M., et al. (författare)
  • Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles : a simulation study
  • 2015
  • Ingår i: SORT - Statistics and Operations Research Transactions. - 1696-2281 .- 2013-8830. ; 39:2, s. 281-308
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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7.
  • Felleki, Majbritt, et al. (författare)
  • Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models
  • 2012
  • Ingår i: Genetics Research. - : Cambridge University Press. - 0016-6723 .- 1469-5073. ; 94:6, s. 307-317
  • Tidskriftsartikel (refereegranskat)abstract
    • 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).
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8.
  • Felleki, Majbritt (författare)
  • Genetic Heteroscedasticity for Domestic Animal Traits
  • 2014
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • 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.
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9.
  • Hallén Sandgren, C, et al. (författare)
  • Homogeneity density scores of quarter milk in automatic milking systems.
  • 2021
  • Ingår i: Journal of Dairy Science. - : American Dairy Science Association. - 0022-0302 .- 1525-3198. ; 104:9, s. 10121-10130
  • Tidskriftsartikel (refereegranskat)abstract
    • Milk quality and clinical mastitis in dairy cows are monitored by detecting visually abnormal milk. A standardized method to evaluate clots in milk and studies of the incidence and dynamics of clots in milk at the quarter level are lacking. We validated a method to score clot density in quarter milk samples and describe the prevalence and dynamics of the density scores between consecutive samplings and periods in 4 farms with automatic milking systems. Using in-line filters, we collected quarter milk samples at each milking during 3 periods of 30 h each in each farm. Clot density was scored based on coverage of the filter area as 0 (negative), 1 (trace), 2 (mild), 3 (moderate), 4 (heavy), and 5 (very heavy). The score for a specific quarter and milking is referred to as the quarter milking score (QMS). Three assessors independently scored 902 images of filter samples with a Fleiss kappa value of 0.72. In total, 21,202 quarter milk samples from 5,398 milkings of 621 cows were collected. Of the quarter filter samples, 2.4% had visible clots, distributed as mild (1.4%), moderate (0.6%), heavy (0.3%), and very heavy (<0.1%, n = 8). Cases with a cow period sum of QMS ≥ 4, corresponding to 9.4% of all periods, harbored 86% and 94% of all QMS of 2 to 5 and 3 to 5, respectively. Of these cases, cows sampled in all 3 periods and clots in only 1 period had a quarter period sum score ≥ 1 in 1.8 different quarters in average. Corresponding numbers for the cows with clots or traces in 2 or 3 periods were 2.2 and 2.5 different quarters, respectively. A QMS of 2 to 5 in the preceding milking increased the chance of a QMS >1 in the following milking, with an average chance of 38%. The probability of a QMS > 1 increased with increasing previous QMS, a higher sum of QMS during the milking period, longer milking interval, and higher lactation number, but decreased with increasing days in milk. Our study showed that the method of clot-density scoring is feasible to perform and reproducible for investigating the occurrence and dynamics of clots in milk. Elevated clot-density scores clustered within certain cows and cow periods and appeared in new quarters of the cows over time. The low recurrence of QMS of 1 and 2 within quarters indicated that QMS 3 could be a reasonable threshold for detecting quarters with abnormal milk that require further attention.
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10.
  • Han, Mengjie, et al. (författare)
  • How do neighbouring populations affect local population change over time?
  • 2013
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • 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.
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