When trying to generate standard errors about fitted values using predict.basglm (i.e., se.fit = TRUE), the function issues an error when data are supplied to newdata:
Error in array(STATS, dims[perm]) :
'data' must be of a vector type, was 'NULL'
In addition: Warning message:
In max(cumDim[cumDim <= lstats]) :
no non-missing arguments to max; returning -Inf
Example which reproduces the behavior:
data(Pima.tr, package="MASS")
data(Pima.te, package="MASS")
Pima.bas = bas.glm(type ~ ., data=Pima.tr, n.models= 2^7, method="BAS",
betaprior=CCH(a=1, b=nrow(Pima.tr)/2, s=0), family=binomial(),
modelprior=uniform())
pred = predict(Pima.bas, newdata=Pima.te, se.fit = TRUE, top=1) # Highest Probability model
Desktop (please complete the following information):
When trying to generate standard errors about fitted values using predict.basglm (i.e., se.fit = TRUE), the function issues an error when data are supplied to newdata:
Error in array(STATS, dims[perm]) : 'data' must be of a vector type, was 'NULL' In addition: Warning message: In max(cumDim[cumDim <= lstats]) : no non-missing arguments to max; returning -Inf
Example which reproduces the behavior:
Desktop (please complete the following information):