XploRe Help : glmlld

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library:	glm
See also:	glmcore

Quantlet:		glmlld
Description:		glmlld computes the first and second derivative of the individual log-likelihood in dependence of the linear index eta and y.

Link:

Tutorial: GLM in XploRe

Usage:	`{ll1,ll2} = glmlld(code,eta,y{,opt})`
Input:
	`code`	text string, the short code for the model (e.g. "bipro" for probit or "noid" for linear model). Append "fs" to the code for the expected ll2 instead of ll2 (-> Fisher scoring algorithm).
	`eta`	n x d matrix, the index values.
	`y`	n x d matrix, the response values.
	`opt`	optional, a list with optional input. "glmopt" can be used to set up this parameter.
	`opt.pow`	scalar, power for power link. If not given, set to 0 (logarithm).
	`opt.nbk`	scalar, extra parameter k for negative binomial distribution. If not given, set to 1 (geometric distribution).
Output:
	`ll1`	n x d matrix, 1st derivative of log-likelihood.
	`ll2`	n x d matrix, 2nd derivative of log-likelihood.

Example:

library("glm") y=1 eta=2 {ll1,ll2}=glmlld("bilo",eta,y) ll1 ll2

Result:

The derivatives of the individual log-likelihood for a logit
model are computed at y=1 and eta=2:
Contents of ll1
[1,]   0.1192
Contents of ll2
[1,] -0.10499

Author: M. Mueller, 20010228