Hello,
I am using the gpls package for modelling vegetation classes.
My problem is that I now want to know which input variables are significant for
the modelling of the classes to recalculate the equation again with just the
selected variables.
I think I can analyse the significance of the variables via their weights.
I used the "gpls1a" term for two group classification. Here my code:
----------------------------------------------------------------------
library(gpls) #
> spex_Y<-read.csv("F:/GPLS/spex_Y.csv", header=TRUE, sep=";")#,
> row.names="ID") #
> spex_X<-read.csv("F:/GPLS/spex_X.csv", header=TRUE, sep=";")#,
> row.names="ID") #
>
> test <- glpls1a(spex_X, spex_Y$A_mell,K.prov=7, br=FALSE)
> names(test)
[1] "coefficients" "convergence" "niter" "family"
[5] "link" "levs" "bias.reduction"
coefficients = regression coefficients
convergence = whether convergence is achieved
niter total = number of iterations
bias.reduction = whether Firth's procedure is used
link = link function, logit is the only one practically implemented now
---------------------------------------------------------------------
But the values (coefficients, convergence, niter, family, link, levs,
bias.reduction) I have got from the gpls1a do not contain any information about
the significance of my input variables.
Does anybody have an idea how I can get information about the significance of
my input values?
This would really help me a lot.
--
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