get_discrepancy {catalytic} | R Documentation |
Compute Discrepancy Measures
Description
This function computes various discrepancy measures between observed and estimated values. It supports different methods including logarithmic error, square error, classification error, and logistic deviance.
Usage
get_discrepancy(
discrepancy_method = c("mean_logarithmic_error", "mean_square_error",
"mean_classification_error", "logistic_deviance"),
family_string = NULL,
X = NULL,
Y = NULL,
coefs = NULL,
est_Y = NULL
)
Arguments
discrepancy_method |
A character string specifying the discrepancy method to use. Options are:
|
family_string |
A GLM family in string (e.g., "binomial") used to compute logistic deviance. |
X |
A matrix of predictor variables. |
Y |
A vector or data frame of observed values. |
coefs |
A vector of coefficients for the GLM model. |
est_Y |
A vector of estimated values. If not provided, it will be computed using |
Value
A numeric value representing the discrepancy between observed and estimated values.