Hi all,
I try to interpolate a data set in the form:
time Erg
0.000000 48.650000
1.500000 56.080000
3.000000 38.330000
4.500000 49.650000
6.000000 61.390000
7.500000 51.250000
9.000000 50.450000
10.500000 55.110000
12.000000 61.120000
18.000000 61.260000
24.000000 62.670000
36.000000 63.670000
48.000000 74.880000
I want to get smoothed splines by using the class gam
The first way I tried , was the following:
> library('mgcv')
> t=read.table('Valuedata', header=T, sep="\t")
> g=gam(Erg~s(time,k=4,fx=TRUE,bs="cr"),data=t)
> plot(g)
The plot shows me 3 curves in the yrange of -20 and 30 and I don't
know, which curve is the result.
The second way I tried was:
> library("gam")
> t=read.table('Valuedata', header=T, sep="\t")
> g=gam(Erg~s(time,3), data=t)
> plot(g)
Error in eval(predvars, data, env) : invalid 'envir' argument
This way I can't see the result and I so I can't see the curve.
My first question:
How can I get the function to calculate the according splines, that are
determined by gam.
I think about a function like:
f(x)=a0+a1+x+a2*x^2+a3*x^3 +smooth(x)
a polynome of rank k, that I can use in an other context. I can find the
fitted.values, the coefficients and the smooth but I can't find the exact
description to calculate the according values.
I want to calculate the interpolations spline in the interval [0,48]
and use maybe 100 - 1000 supporting points.
Or exists a function in R, that gives me these values?
My second question:
I can't find a reason for the error message above.
I have no experience with R, but I program in other languages.
Thanks a lot to everybody who will help me - anna_m!
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