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: gplmopt gplmnoid gplmnoidtest glmnoid

Macro: gplmnoidbiased
Description: biased LM -- gplmnoidbiased computes the biased linear model for the test of a linear model versus a PLM. This is a fast routine using the command sker to obtain kernel estimates.

Reference(s):

Link:
Usage: myfit = gplmnoidbiased(x,t,y,h,b{,opt})
Input:
x n x p matrix, the discrete 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 vector, coefficients b from parametric fit.
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.wx scalar or n x 1 vector, prior weights. If not given, set to 1.
opt.tg ng x 1 vector, a grid for continuous part. If tg is given, the nonparametric function will also be computed on this grid.
opt.nosort integer, if exists and =1, the continuous variables t and the grid tg are assumed to be sorted by the 1st column. Sorting is required by the algorithm! Hence this option should be given only when data are sorted.
opt.off scalar or n x 1 vector, offset in predictor.
Output:
myfit.m n x 1 vector, biased version of m0
myfit.mg ng x 1 vector, biased version of m0g

Example:
library("glm") 
library("gplm")
;==========================
;  simulate data 
;==========================
n=100
b=1|2
p=rows(b)
x=2.*uniform(n,p)-1
t=sort(2.*uniform(n)-1,1)
m=0.5*cos(pi.*t)+0.5*t
y=x*b+m+normal(n)./2
;==========================
;  parametric (ls) fit 
;==========================
pf=glmnoid(x~t~matrix(n),y)
b0 =pf.b[1:p]
gamma0 =pf.b[p+1:rows(pf.b)]
m0 =(t~matrix(n))*gamma0
;==========================
;  semiparametric fit 
;==========================
h=0.6
yb=x*b0+m0
bf=gplmnoidbiased(x,t,yb,h,b0)
pic=createdisplay(1,1)
show(pic,1,1,t~m,t~m0,t~bf.m)
Result:
A biased linear fit for E[y|x,t] is computed. bf.m contains  
the biased linear fit evaluated at observations t. This is 
needed for the test of a linear model vs. a partially linear. 
bf.m is displayed together with the true and the linear fit.

Library: gplm
See also: gplmopt gplmnoid gplmnoidtest glmnoid

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, 970523
(C) MD*TECH Method and Data Technologies, 28.6.1999