Fits a Generalized Additive Model (GAM) for each environmental variable in a data.frame against an ordination.
# S3 method for dsvord
calibrate(dsvord,site,dims=1:ncol(dsvord$points),
family='gaussian',gamma=1,keep.models=FALSE)A list object with vector elements aic, dev.expl, adj.rsq, and fitted value matrix. Optionally, if keep.models is TRUE, a list with all of the GAM models fitted. List element aic gives the model AICs for each variable, dev.expl gives the deviance explained, adj.rsq gives the adjusted r-Squared, and fitted gives the expected value of each variable in each sample unit.
an ordination object of class dsvord
a matrix or data.frame with sample units as rows and environmental variables as columns
the specific dimensions of the ordination to consider
the error distribution specifier for the GAM function
the gamma parameter to control fitting GAM models
a switch to control saving the individual GAM models
David W. Roberts droberts@montana.edu http://ecology.msu.montana.edu/droberts/droberts.html
The calibrate function sequentially and independently fits a GAM model for each environmental variable as a function of ordination coordinates, using the family and gamma specifiers supplied in the function call, or their defaults. The model fits two or three dimensional models; if the length of dims is greater than three the dimensions are truncated to the first three chosen.
predict for the complementary function that fits GAM models for species
data(bryceveg)
dis.man <- dist(bryceveg,method="manhattan")
demo.nmds <- nmds(dis.man,k=4)
if (FALSE) res <- calibrate(demo.nmds,brycesite[,c(2,4,7,12)],minocc=10)
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