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: gplm
See also: gplmest gplmstat

Macro: gplmout
Description: gplmout creates a nice output display for gplm.

Link:
Usage: gplmout(code,x,t,y,h,b,bv,m,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.
t n x q matrix, the continuous predictor variables.
y n x 1 vector, the response variables.
h q x 1 vector, the bandwith.
b p x 1, estimated coefficients.
bv p x p matrix, estimated covariance matrix for coeff.
m n x 1 vector, estimated nonparametric part.
stat list, containing statistics produced by gplm macros.
opt optional, a list with optional input. The macro "gplmopt" can be used to set up this parameter. The order of the list elements is not important. Parameters which are not given are replaced by defaults (see below).
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, name for the output. If not given, "gplmout" 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:
gplmOutput 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.
gplmout or opt.name+"out", string vector, global, containing estimation result in the left panel as text.

Example:
library("gplm") 
n=100
b=1|2
p=rows(b)
x=2.*uniform(n,p)-1
t=sort(2.*uniform(n)-1,1)
m=cos(pi.*t)
y=x*b+m+normal(n)./2
{b,bv,m,mg,stat}=gplmest("noid",x,t,y,0.6)
gplmout("noid",x,t,y,0.6,b,bv,m,stat)
Result:
After fitting a partially linear regression with gplmest, a 
display is created, which contains the estimated coefficients,
their standard errors and t-values as well as the statistics
determined by gplmest on the left panel. The right panel
of the display shows a plot of x*b+m vs. y together with
a plot of x*b+m vs. the link function.

Library: gplm
See also: gplmest gplmstat

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

Author: Marlene Mueller, 2000/05/10
(C) MD*TECH Method and Data Technologies, 17.8.2000