Mixing
R - likelihood ratio test with one model
I should perform a likelihood ratio test on the following null hypothesis :
α = Aψ
where α and A (p * m) are known vectors. ψ (m*r) is a matrix of free parameters.
The likelihood ratio test is asymptotically distributed as χ2 with r(p-m) degrees of freedom.
What I don't understand is that normally, LR tests compare 2 models. But here it's not the case?
I tried this on R but not sure of it since I didn't include the ψ matrix, that confuses me.
A=c(1,0)
testo1<-G$othog.alpha ~A
lrtest(testo1)
G$othog.alpha is my vector of α (2 values).
r hypothesis-test
asked Nov 19 '18 at 15:36
Narjems
409
add a comment |
I should perform a likelihood ratio test on the following null hypothesis :
α = Aψ
where α and A (p * m) are known vectors. ψ (m*r) is a matrix of free parameters.
The likelihood ratio test is asymptotically distributed as χ2 with r(p-m) degrees of freedom.
What I don't understand is that normally, LR tests compare 2 models. But here it's not the case?
I tried this on R but not sure of it since I didn't include the ψ matrix, that confuses me.
A=c(1,0)
testo1<-G$othog.alpha ~A
lrtest(testo1)
G$othog.alpha is my vector of α (2 values).
r hypothesis-test
asked Nov 19 '18 at 15:36
Narjems
409
add a comment |
I should perform a likelihood ratio test on the following null hypothesis :
α = Aψ
where α and A (p * m) are known vectors. ψ (m*r) is a matrix of free parameters.
The likelihood ratio test is asymptotically distributed as χ2 with r(p-m) degrees of freedom.
What I don't understand is that normally, LR tests compare 2 models. But here it's not the case?
I tried this on R but not sure of it since I didn't include the ψ matrix, that confuses me.
A=c(1,0)
testo1<-G$othog.alpha ~A
lrtest(testo1)
G$othog.alpha is my vector of α (2 values).
r hypothesis-test
asked Nov 19 '18 at 15:36
Narjems
409
I should perform a likelihood ratio test on the following null hypothesis :
α = Aψ
where α and A (p * m) are known vectors. ψ (m*r) is a matrix of free parameters.
The likelihood ratio test is asymptotically distributed as χ2 with r(p-m) degrees of freedom.
What I don't understand is that normally, LR tests compare 2 models. But here it's not the case?
I tried this on R but not sure of it since I didn't include the ψ matrix, that confuses me.
A=c(1,0)
testo1<-G$othog.alpha ~A
lrtest(testo1)
G$othog.alpha is my vector of α (2 values).
r hypothesis-test
r hypothesis-test
asked Nov 19 '18 at 15:36
Narjems
409
asked Nov 19 '18 at 15:36
Narjems
409
asked Nov 19 '18 at 15:36
Narjems
409
asked Nov 19 '18 at 15:36
Narjems
409
asked Nov 19 '18 at 15:36
Narjems
409
409
add a comment |
add a comment |
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