e.g...
b <- gam(Y~s(X)) ## fit
gam.check(b) ## check
fitted(b) ## fitted values
predict(b,newdata=data.frame(X=c(15,16))) ## predictions at new X
.... see ?predict.gam
On 14/03/14 23:24, Parviz Zare wrote:
Dear Sir,
How I can obtain the predicted values of Y variable with fitting smooth spline
regressions (in GAMs) using R software?
in my research, temperature (X variable) is as smoother and fish catch values
(Y variable) is as response
variable.
I would be grateful if you could help me.
Yours sincerely Parviz
________________________________
From: Douglas Bates <ba...@stat.wisc.edu>
Sent: Saturday, 15 March 2014, 0:23:03
Subject: Re: smooth spline
A question such as this should be sent to the R-help@R-project.org mailing
list, but first I would advise you to clarify your question and, most
helpfully, include information on the version of R and of any R packages you
are using. This can be obtained by entering
sessionInfo()
after you have fit your model. You could cut-and-paste the results that are
shown as the result of that statement.
Dear Douglas,
I am going to fit smooth spline regressions between
an environmental variable (as a smoother) and CPUA (fish catch value) as a
response
variable using R software. Then, the regressions were used to calculate
Suitability
index (SI):
Where, is the predicted value of CPUA; and are the minimum and maximum
values of the
predicted CPUA values, respectively.
I have an R code for thin regression, but there
is one problem. When I run it, there is in output only graph. But I need to the
predicted value of CPUA () to to
calculate Suitability index (SI).
Please look at the attached file.
I would be grateful if you could help me.
Yours sincerely
Parviz
[[alternative HTML version deleted]]
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