View source: R/testcoef.pois.env.R
testcoef.pois.env | R Documentation |
This function tests the null hypothesis L * beta = A versus the alternative hypothesis L * beta ~= A, where beta is estimated under the envelope model in poisson regression.
testcoef.pois.env(m, L, A)
m |
A list containing estimators and other statistics inherited from pois.env. |
L |
The matrix multiplied to beta on the left. It is a d1 by p matrix, while d1 is less than or equal to p. |
A |
The matrix on the right hand side of the equation. It is a d1 by 1 matrix. |
Note that inputs L
and A
must be matrices, if not, use as.matrix
to convert them.
This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A. The beta is estimated by the envelope model in predictor space. If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0. The test statistic used is vec(L beta - A) hatSigma^-1 vec(L beta - A)^T, where beta is the envelope estimator and hatSigma is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1.
The output is a list that contains following components.
chisqStatistic |
The test statistic. |
dof |
The degrees of freedom of the reference chi-squared distribution. |
pValue |
p-value of the test. |
covMatrix |
The covariance matrix of vec(L beta). |
data(horseshoecrab)
X1 <- as.numeric(horseshoecrab[ , 1] == 2)
X2 <- as.numeric(horseshoecrab[ , 1] == 3)
X3 <- as.numeric(horseshoecrab[ , 1] == 4)
X4 <- as.numeric(horseshoecrab[ , 2] == 2)
X5 <- as.numeric(horseshoecrab[ , 2] == 3)
X6 <- horseshoecrab[ , 3]
X7 <- horseshoecrab[ , 5]
X <- cbind(X1, X2, X3, X4, X5, X6, X7)
Y <- horseshoecrab[ , 4]
m <- pois.env(X, Y, 1)
L <- diag(7)
A <- matrix(0, 7, 1)
test.res <- testcoef.pois.env(m, L, A)
test.res
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