XploRe Help : intertest1

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:	gam
See also:	intest interact intertest2

Quantlet:		intertest1
Description:		intertest1 is testing for interaction of x_1 and x_2 in an additive regression model. It is looking at the interation estimate and using wild bootstrap. For details see Sperlich, Tjostheim, Yang (1997)

Usage:	`testt = intertest1(t,y,h,g{,opt{,file}})`
Input:
	`t`	n x p matrix , the observed explanatory variable where the directions of interest have to be the first and second column
	`y`	n x 1 vector , the observed response variables
	`h`	p x 1 or 1 x 1 matrix , chosen bandwidth for the directions of interest in the estimation step
	`g`	p x 1 or 1 x 1 matrix , chosen bandwidth for the directions not of interest in the estimation step
	`opt.hyp`	pp x 2 matrix, in the rows have to be all pairs of indices for interactions which shall be included in the hypothesis model. Thus (1,2) must not be a row of hyp.
	`opt.boot`	integer, number of bootstrap replications, default=249.
	`opt.hb`	scalar, bandwidth multiplicator for the bootstrap step. When the test statistics are calculated we take bandwidths hhb and ghb instead of h, g. Default is 1.
	`opt.weight`	n x 1 vector, weights for the test statistics. Default is weight 1 for all.
	`file`	string, file name of output, if an output of the function estimates is wished
Output:
	`testt`	string object, a table of results

Example:

library("gam") randomize(12345) n = 50 t = uniform(n,3)*2-1 g1 = 2*t[,1] g2 = t[,2]^2 - mean(t[,2]^2) g3 = sin(3*t[,3]) g12 = t[,1].*t[,2] y = g1+g2+g3+g12+normal(n)*sqrt(0.5) h = #(0.9,0.9,0.7) g = #(1.0,1.0,0.9) boot = 99 hb = 1.1 weight= matrix(n)-prod((abs(t[,1:2]).>0.85),2) opt = list(boot,hb,weight) intertest1(t,y,h,g,opt)

Result:

table of test results

Author: S. Sperlich, 19970723