# Poisson regression with spatially correlated random effects
ADMB Files
Code: spatial.tpl Data: spatial.dat Initial values: spatial.pin Expected Results: spatial.par
| ### Model description Our data yi,j are observed on a regular 10x10 grid of points: {i,j=1,...,10}. It is assumed that yi,j ~ Poisson(li,j), where log(li,j) = Xi,jb + ei,j. Here, Xi,jb is a linear predictor and ei,j are Gaussian random variables with covariance cov(ei1,j1,ei2,j2) = s2 exp(a-1 d), where d is the Euclidean distance.