likelihood ratio test 中文應該是 似然比檢驗 suppose you have two model one restricted model and the other is a unrestricted model under assumption: H0:theta=theta0 and H1: theta=theta1; then by constructing two likelihood function L1(theta0|x)(unrestricted) and L2(theta1|x)(restricted) compute the likelihood ratio as LR(x)=L1(theta0|x)/L2(theta1|x) reject H0 if {x<=c}; normally, we use -2ln(LR(x))~chi-squared(dim(Theta1)-dim(Theta0))
likelihood ratio test 中文應該是 似然比檢驗 suppose you have two model one restricted model and the other is a unrestricted model under assumption: H0:theta=theta0 and H1: theta=theta1; then by constructing two likelihood function L1(theta0|x)(unrestricted) and L2(theta1|x)(restricted) compute the likelihood ratio as LR(x)=L1(theta0|x)/L2(theta1|x) reject H0 if {x<=c}; normally, we use -2ln(LR(x))~chi-squared(dim(Theta1)-dim(Theta0))