K fold cross validation for ctStanFit objects
K fold cross validation for ctStanFit objects
ctLOO( fit, folds = 10, cores = 2, parallelFolds = FALSE, subjectwise = ifelse(length(unique(fit$standata$subject)) > folds, TRUE, FALSE), keepfirstobs = FALSE )
fit |
ctStanfit object |
folds |
Number of cross validation splits to use – 10 folds implies that the model is re-fit 10 times, each time to a data set with 1/10 of the observations randomly removed. |
cores |
Number of processor cores to use. |
parallelFolds |
compute folds in parallel or use cores to finish single folds faster. parallelFolds will use folds times as much memory. |
subjectwise |
drop random subjects instead of data rows? |
keepfirstobs |
do not drop first observation (more stable estimates) |
list
ctLOO(ctstantestfit)
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