| infmat_bet {bbreg} | R Documentation |
infmat_bet
Description
Function to compute standard errors based on the Fisher information matrix for the beta regression. This function can also provide the Fisher's information matrix.
Usage
infmat_bet(theta, z, x, v, link.mean, link.precision, information = FALSE)
Arguments
theta |
vector of parameters (all coefficients: kappa and lambda). |
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. |
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". |
information |
optionally, a logical parameter indicating whether the Fisher's information matrix should be returned |
Value
Vector of standard errors or Fisher's information matrix if the parameter 'information' is set to TRUE.