Jan,
Could you send the exact gam call and exact vis.gam call that did this
please? Also, if 'm' denotes your fitted model, what result does
'fitted(m)' give? and what is the output from print(m)?
best,
Simon
On 07/30/2012 09:19 PM, janvanhove wrote:
Hi everyone,
I ran a binomial GAM consisting of a tensor product of two continuous
variables, a continuous parametric term and crossed random intercepts on a
data set with 13,042 rows. When trying to plot the tensor product with
vis.gam(), I get the following error message:
Error in persp.default(m1, m2, z, col = col, zlim = c(min.z, max.z), xlab =
view[1], :
invalid 'z' limits
In addition: Warning messages:
1: In max(z, na.rm = TRUE) :
no non-missing arguments to max; returning -Inf
2: In min(fv$fit, na.rm = TRUE) :
no non-missing arguments to min; returning Inf
3: In max(fv$fit, na.rm = TRUE) :
no non-missing arguments to max; returning -Inf
When I specify zlim in vis.gam, the 3D frame of the graph is plotted, but
not the tensor product surface itself, and vis.gam() returns the following
warning:
Warning message:
In max(z, na.rm = TRUE) : no non-missing arguments to max; returning -Inf
Unfortunately, I cannot replicate these errors with made-up data nor with a
random subset of the full data set. When I run the model WITHOUT the third
variable, everything works fine. Can anyone give me some pointers?
Thank you!
Jan
R version: 2.15.1 (32 bit Linux)
mgcv, version 1.7-19
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