Wald test
rwd = gmmWald(rgmm,R,r,np)
* rgmm = tlist result for unrestricted estimation
* R = is the (s x #parameters) R matrix of linear constraints in Rb = r
* r = (s x 1) r vector in Rb = r
* np = 'noprint' if the user does not want to print the results
* rwd = a tlist which arguments can be:
-rwd('chistat') = test statisitic
-rwd('pvalue') = pvalue of the test
-rwd('df') = number of restrictions
X = [ones(1000,1) grand(1000,1,'nor',0,1) grand(1000,1,'nor',0,1)]; b = [0;1;-1]; e = grand(1000,1,'nor',0,1); y = X*b + e; gmmopt = tlist(['gmm';'momt';'jake';'prt';'gmmit';'S']); gmmopt('prt')=1; gmmopt('gmmit') = 1; gmmopt('S')='W'; gmmopt('momt')='gmmLinM'; gmmopt('jake')='gmmLinJ'; b0=zeros(3,1); uout=gmm('y',gmmopt,'exo=''X''','ivar=''X''','parm0=b0'); R = [1 0 0];r = 0; rw=gmmWald(uout,R,r); // Example taken from gmmLin_d(): test if the first parameter is null | ![]() | ![]() |