statmod (version 1.2.0)

glmgam.fit: Gamma Generalized Linear Model with Identity Link

Description

Estimates a gamma generalized linear model with identity link using Fisher scoring with Levenberg damping.

Usage

glmgam.fit(X, y, start=NULL, tol=1e-6, maxit=50, trace=FALSE)

Arguments

X

design matrix, assumed to be of full column rank. Missing values not allowed.

y

numeric vector of responses. Negative or missing values not allowed.

start

numeric vector of starting values for the regression coefficients

tol

small positive numeric value giving convergence tolerance

maxit

maximum number of iterations allowed

trace

logical value. If TRUE then output diagnostic information at each iteration.

Value

• List with the following components:
• coefficients
  numeric vector of regression coefficients
• fitted
  numeric vector of fitted values
• deviance
  residual deviance
• maxit
  input maximum number of iterations
• iter
  number of iterations used to convergence. If convergence was not achieved then iter is set to maxit+1.

Details

This function is similar to glm.fit(X,y,family=Gamma(link="identity")) but has more secure convergence. This function is used by randomizedBlockFit.

Examples

y <- rgamma(10,shape=5)
X <- cbind(1,1:10)
fit <- glmgam.fit(X,y,trace=TRUE)