kfold_predict {brms} | R Documentation |
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)