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GLMM’s on large spatial grids

by Hans Julius Skaug — last modified Jan 12, 2010 01:43 PM

It has for a long time been possible to fit GLMMs (Generalized Linear Mixed Models) in ADMB-RE. A typical example is correlated count data with Poisson distribution. However, when the observation are located on a spatial grid the number of latent variables (random effects in the ADMB-RE terminology) grows quadratically in the number of grid points in each geographical direction. The large number of random effects causes a computational challenge.

File Model description — by Hans Julius Skaug — last modified Jan 12, 2010 01:33 PM
Describes the technical details about how the model is implemented in ADMB using the sparse matrix feature
File A practical example — by Hans Julius Skaug — last modified Jan 12, 2010 01:41 PM
If you find the model description hard to read, you may find this a gentler description (will be submitted to the ADMB Newsletter).
File ADMB files — by Hans Julius Skaug — last modified Apr 29, 2010 01:23 PM
tpl-file and data files needed for running the example. gmrf10.dat contains a 10x10 grid, and should run fast. gmrf100.dat contains a 100x100 grid, and will require >8Gb of memory. In addition you should use the command line ./gmrf -est -ilmn 5 -ind gmrf100.dat -shess -ndi 10000000 -noinit -gbs 100000000 Note: Current research on the ADMB source code has shown that relatively small modifications will make it feasible to fit a 200x200 grid on a 1.5 Gb machine. These improvements will find their way into the official ADMB source soon.
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