Predictions from K-Fold Cross-Validation
Compute and evaluate predictions after performing K-fold
cross-validation via kfold.
kfold_predict(x, method = c("predict", "fitted"), resp = NULL, ...)x |
Object of class |
method |
The method used to make predictions. Either |
resp |
Optional names of response variables. If specified, predictions are performed only for the specified response variables. |
... |
Further arguments passed to |
A list with two slots named 'y' and 'yrep'.
Slot y contains the vector of observed responses.
Slot yrep contains the matrix of predicted responses,
with rows being posterior draws and columns being observations.
## Not run:
fit <- brm(count ~ zBase * Trt + (1|patient),
data = epilepsy, family = poisson())
# perform k-fold cross validation
(kf <- kfold(fit, save_fits = TRUE, chains = 1))
# define a loss function
rmse <- function(y, yrep) {
yrep_mean <- colMeans(yrep)
sqrt(mean((yrep_mean - y)^2))
}
# predict responses and evaluate the loss
kfp <- kfold_predict(kf)
rmse(y = kfp$y, yrep = kfp$yrep)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.