gradtheta_bes {bbreg}

gradtheta_bes

Description

Function to calculate the gradient of the Q-function, which is required for optimization via optim. This option is related to the bessel regression.

Usage

gradtheta_bes(theta, wz, z, x, v, link.mean, link.precision)

Arguments

theta

vector of parameters (all coefficients: kappa and lambda).

wz

parameter representing E(1/W_i|Z_i = z_i, theta).

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".

Value

vector representing the output of this auxiliary gradient function for the bessel case.