Any chance you could send me the data and exact code that produces this
(I'll only use the data for investigating this issue of course - often
data with the predictor replaced by noise will produce the same error,
if sending the raw data is a problem)?
best, Simon (mgcv maintainer)
On 20/09/16 17:22, Fotis Fotiadis wrote:
Hi all
I am using the bam function of the mgcv package to model behavioral data of
a learning experiment. To model individual variation in learning rate, I am
testing models with (a) by-participant random intercepts of trial, (b)
by-participant random slopes and random intercepts of trial, and (c)
by-participant random smooth terms.
While all (a) and (c) models converge, I am getting an error for every
possible variation of a model with random intercepts and random slopes. For
example:
m1.rs<-bam(acc~ 1 + igc + s(ctrial) + s(sbj, bs="re") + s(ctrial, sbj,
bs="re") , data=data_a, family=binomial)
Error in G$smooth[[i]]$first.para:G$smooth[[i]]$last.para :
argument of length 0
Any idea on what that error might be?
Thank you in advance for your time.
Fotis
P.S.: R version: 3.3.1, mgcv version: 1.8.15
--
Simon Wood, School of Mathematics, University of Bristol BS8 1TW UK
+44 (0)117 33 18273 http://www.maths.bris.ac.uk/~sw15190
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