Hello everyone.



I am doing a logistic gam (package mgcv) on a pretty large dataframe
(130.000 cases with 100 variables).

Because of that, the gam is fitted on a random subset of 10000. Now when I
want to predict the values for the rest of the data, I get the following
error:





> gam.basis_alleakti.1.pr=predict(gam.basis_alleakti.1,

+
newdata=activisale_join[gam.basis_alleakti.1.complete_cases,all.vars(gam.b
asis_alleakti.1.formula)],type="response")

Error in predict.gam(gam.basis_alleakti.1, newdata =
activisale_join[gam.basis_alleakti.1.complete_cases,  :

  number of items to replace is not a multiple of replacement length





The following is the code:

#formula with some factors and a lot of variables to be fitted

gam.basis_alleakti.1.formula=as.formula( paste("verlängerung ~“,

      paste( names(activisale_join)[c(2:10)], collapse="+"), ##factors


paste("s(",names(activisale_join)[c(17,19:29,31:42,44)],")",
collapse="+")) # numeric variables, all count data

)



# complete cases

gam.basis_alleakti.1.complete_cases =
complete.cases(activisale_join[,all.vars(gam.basis_alleakti.1.formula) ])



# modell fitting works on random subset

gam.basis_alleakti.1=bam(gam.basis_alleakti.1.formula,

                         data = activisale_join[subset.10000, ], family=
"binomial")



# error, no idea why

gam.basis_alleakti.1.pr=predict(gam.basis_alleakti.1,
newdata=activisale_join[gam.basis_alleakti.1.complete_cases,
],type="response")





the prediction on the same subset (subset.10000) works.





It could be that this error is somewhat similar to that described as
sidequestion in

http://r.789695.n4.nabble.com/gamm-tensor-product-and-interaction-td452618
8.html, where simon answered the following:



“>  Here is the error message I obtain:
>
vis.gam(gm1$gam,plot.type="contour",n.grid=200,color="heat",zlim=c(0,4))
>  Error in predict.gam(x, newdata = newd, se.fit = TRUE, type = type) :
number of items to replace is not a multiple of replacement length
- hmm, possibly a bug. I'll look into it.

best,
Simon“



All the best



Julian



Ps.: > version
               _
platform       x86_64-w64-mingw32
arch           x86_64
os             mingw32
system         x86_64, mingw32
status
major          3
minor          0.1
year           2013
month          05
day            16
svn rev        62743
language       R
version.string R version 3.0.1 (2013-05-16)
nickname       Good Sport



package mgcv version 1.7-22




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