calibrate | R Documentation |
Fits a Generalized Additive Model (GAM) for each environmental variable in a data.frame against an ordination.
## S3 method for class 'dsvord'
calibrate(ord,site,dims=1:ncol(ord$points),
family='gaussian',gamma=1,keep.models=FALSE,...)
ord |
an ordination object of class dsvord |
site |
a matrix or data.frame with sample units as rows and environmental variables as columns |
dims |
the specific dimensions of the ordination to consider |
family |
the error distribution specifier for the GAM function |
gamma |
the gamma parameter to control fitting GAM models |
keep.models |
a switch to control saving the individual GAM models |
... |
arguments to pass |
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.
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.
David W. Roberts droberts@montana.edu
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)
## Not run: res <- calibrate(demo.nmds,brycesite[,c(2,4,7,12)],minocc=10)
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