| gam.sig.start {spgam} | R Documentation |
~~ A concise (1-5 lines) description of what the function does. ~~
gam.sig.start(form, gam.data, pts, region, h, ngrid)
form |
~~Describe form here~~ |
gam.data |
~~Describe gam.data here~~ |
pts |
~~Describe pts here~~ |
region |
~~Describe region here~~ |
h |
~~Describe h here~~ |
ngrid |
~~Describe ngrid here~~ |
~~ If necessary, more details than the description above ~~
~Describe the value returned If it is a LIST, use
comp1 |
Description of 'comp1' |
comp2 |
Description of 'comp2' |
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~~further notes~~
~Make other sections like Warning with section{Warning }{....} ~
~~who you are~~
~put references to the literature/web site here ~
~~objects to See Also as help, ~~~
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function(form,gam.data,pts,region,h,ngrid)
{
################ Tolerance interval for GAM ####################
# Let gam.data be original data used for doing gamfit
# Let fitted.gam be the result of doing a gamfit
# Let h be chosen smoothing parameter
# sets things up for doing signicance...
formul=formula(form)
termos<-terms(formul)
at<-as.character(attr(termos,"variables"))[-1]
data<-as.data.frame(as.matrix(gam.data[,at]))
fit=glm(formul,family=binomial,data=data)
prob=predict(fit,type='response')
fit=gamfit(form,gam.data,pts=pts,region=region,h=h,ngrid=ngrid)
surf.est=fit$g2est$z
list(prob=prob,surf.est=surf.est,h=h,x=fit$g2est$x,y=fit$g2est$y,
tvalobs=mean(fit$g2^2))
}