| pred_accuracy_bet {bbreg} | R Documentation |
Function to calculate the Residual Sum of Squares for partitions (training and test sets) of the data set. Residuals are calculated here based on the beta regression.
pred_accuracy_bet(
residual,
kap,
lam,
z,
x,
v,
ntest,
predict,
epsilon,
link.mean,
link.precision
)
residual |
Character indicating the type of residual ("pearson", "score" or "quantile"). |
kap |
coefficients in kappa related to the mean parameter. |
lam |
coefficients in lambda related to the precision parameter. |
z |
response vector with 0 < z_i < 1. |
x |
matrix containing the covariates for the mean submodel. Each column is a different covariate. |
v |
matrix containing the covariates for the precision submodel. Each column is a different covariate. |
ntest |
number of observations in the test set for prediction. |
predict |
number of partitions (training and test sets) to be evaluated. |
epsilon |
tolerance parameter used in the Expectation-Maximization algorithm for the training data set. |
link.mean |
a string containing the link function for the mean. The possible link functions for the mean are "logit","probit", "cauchit", "cloglog". |
link.precision |
a string containing the link function the precision parameter. The possible link functions for the precision parameter are "identity", "log", "sqrt", "inverse". |
Vector containing the RSS for each partition of the full data set.
score_residual_bet, quantile_residual_bet, envelope_bet