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Fitting conditional...
Fitting conditional and simultaneous autoregressive spatial models in hglm
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- Alam, Moudud, 1976- (author)
- Högskolan Dalarna,Statistik
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- Rönnegård, Lars (author)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Högskolan Dalarna,Statistik,Institutionen för husdjursgenetik (HGEN),Institutionen för kliniska vetenskaper (KV),Department of Animal Breeding and Genetics,Department of Clinical Sciences
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- Shen, Xia (author)
- Karolinska Institutet,Karolinska Institute
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(creator_code:org_t)
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- 2015
- 2015
- English.
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In: The R Journal. - 2073-4859. ; 7:2, s. 5-18
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Abstract
Subject headings
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- 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.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- Allmänt Mikrodataaanalys - metod
- General Microdata Analysis - methods
Publication and Content Type
- ref (subject category)
- art (subject category)
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