XploRe Help : glmout

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:	glmest glmstat doglm

Quantlet:		glmout
Description:		glmout creates a nice output display for GLM.

Link:

Tutorial: GLM in XploRe

Usage:	`glmout(code,x,y,b,bv,stat{,opt})`
Input:
	`code`	text string, the short code for the model (e.g. "bilo" for logit or "noid" for ordinary PLM).
	`x`	n x p matrix, the predictor variables.
	`y`	n x 1 vector, the response variables.
	`b`	p x 1, estimated coefficients.
	`bv`	p x p, estimated covariance of b.
	`stat`	list, containing statistics produced by glm functions
	`opt`	optional, a list with optional input. "glmopt" can be used to set up this parameter. The order of the list elements is not important.
	`opt.weights`	string, type of weights. Can be "frequency" for replication counts, or "prior" (default) for prior weights in weighted regression.
	`opt.wx`	scalar or n x 1 vector, frequency or prior weights. If not given, set to 1.
	`opt.off`	scalar or n x 1 vector, offset in linear predictor. If not given, set to 0.
	`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).
	`opt.nopic`	integer, if exists and =1, the output display is not produced.
	`opt.name`	string, prefix for the output. If not given, "glm" is used.
	`opt.xvars`	p x 1 string vector, variable names for the output. Note, that only up to 15 characters are used.
	`opt.title`	string, title for the output. If not given, a default is set.
Output:
	`glmOutput`	or opt.name+"Output", display, containing estimation result in the left panel and a plot of the index x*b{+off} vs. y (vs. y./wx for binomials) and a plot of the index vs. the link function.
	`glmout`	or opt.name+"out", string vector, global, containing estimation result in the left panel as text.

Example:

library("glm") n=100 b=1|2 p=rows(b) x=2.*uniform(n,p)-1 y=x*b+normal(n)./2 {b,bv,stat}=glmest("noid",x,y) glmout("noid",x,y,b,bv,stat)

Result:

After fitting a linear regression with glmest, a display
is created, which contains the estimated coefficients,
their standard errors and t-values as well as the statistics
determined by glmest on the left panel. The right panel
of the display shows a plot of x*b vs. y together with
a plot of x*b vs. the link function.

Author: M. Mueller, 20010228