TY - JOUR JF - srtc-jsri JO - JSRI VL - 14 IS - 2 PY - 2018 Y1 - 2018/3/01 TI - Parameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation TT - ​براورد پارامترها در مدل‌های آمیخته‌ی خطی تعمیم‌یافته‌ی فضایی با اثرهای تصادفی چوله‌گاوسی با استفاده از تقریب لاپلاس N2 - Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that random effects have Gaussian distribution, but the assumption is questionable. This assumption is replaced in the present work, using a skew Gaussian distribution for the latent variables, which is more flexible and includes Gaussian distribution. We examine the proposed method using a real discrete data set. SP - 157 EP - 169 AU - Hosseini Shojaei, Seyed Reza AU - Waghei, Yadollah AU - Mohammadzadeh, Mohsen AD - KW - Laplace approximation KW - multivariate skew Gaussian KW - random effects KW - SGLM KW - spatial data. UR - http://jsri.srtc.ac.ir/article-1-273-en.html DO - 10.29252/jsri.14.2.157 ER -