[R] gamm (package mgcv) with large datasets

[Julian Burgos]

Dear list,

I am interested in fitting a Generalized Additive Mixed Model with 
spatially correlated errors to a large, spatially indexed, data set 
(~4000 observations).

My initial analysis was a Generalized Additive Model that included a two 
dimensional smooth term to model spatially correlated effect (i.e. 
s(latitude,longitude)).  The problem is that the residuals of this model 
are still spatially correlated, so it seems that I should use a GAMM in 
which the spatial autocorrelation is modeled explicitly.

The problem is that, as stated in the documentation of the mgcv package, 
my dataset is too large for the gamm function.  Is anybody aware of an 
alternative approach to analyze this data?


 
Julian M. Burgos

Fisheries Acoustics Research Lab
School of Aquatic and Fishery Science
University of Washington

1122 NE Boat Street
Seattle, WA  98105 

Phone: 206-221-6864