Function to compute standard errors based on the Fisher information matrix for the bessel regression. This function can also provide the Fisher's information matrix.
infmat_bes(theta, z, x, v, link.mean, link.precision, information = FALSE)vector of parameters (all coefficients: kappa and lambda).
response vector with 0 < z_i < 1.
matrix containing the covariates for the mean submodel. Each column is a different covariate.
matrix containing the covariates for the precision submodel. Each column is a different covariate.
a string containing the link function for the mean. The possible link functions for the mean are "logit","probit", "cauchit", "cloglog".
a string containing the link function the precision parameter. The possible link functions for the precision parameter are "identity", "log", "sqrt", "inverse".
optionally, a logical parameter indicating whether the Fisher's information matrix should be returned
Vector of standard errors or Fisher's information matrix if the parameter 'information' is set to TRUE.