XploRe Help : glmplot

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:	glminvlink

Quantlet:		glmplot
Description:		glmplot creates a display and plots for a one-dimensional explanatory variable: the distribution, a scatterplot of the marginal influence versus the response and a scatterplot of the variabel versus the response.

Link:

Tutorial: GLM in XploRe

Usage:	`glmplot(x,y{,opt})`
Input:
	`x`	n x 1 matrix, explanatory variable.
	`y`	n x 1 response.
	`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.code`	text string, the short code for the model (e.g. "bilo" for logit or "noid" for ordinary LS).
	`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.pow`	optional, power for power link.
	`opt.nbk`	scalar, extra parameter k for negative binomial distribution. If not given, set to 1 (geometric distribution).
	`opt.xvars`	scalar string vector, variable name for the output.
	`opt.name`	string, prefix for the output. If not given, "glm" is used.
Output:
	`glmPlot or opt.name+"Plot"`	display, containing the distribution of x in the first window (histogram/density), the marginal influence of x on y in the second and a scatterplot of x versus y in the third.

Example:

library("glm") x=normal(500) y=(x+normal(500) >0) ; probit model opt=glmopt("code","bipro") glmplot(x,y,opt)

Result:

The density of x, the marginal influence of x and a
scatter plot of x and y.

Author: M. Mueller, 20010228