mdscore {mdscore} | R Documentation |
Modified score test for generalized linear models
Description
Computes the modified score test based for the coefficients of a generalized linear model.
Usage
mdscore(model = model, X1 = X1, phi = NULL)
Arguments
model |
an object that stores the results of |
X1 |
the matrix with the columns of the model matrix X that correspond to the coefficients being specified in the null hypothesis. |
phi |
the precision parameter. |
Details
The object fit.model
is obtained using the usual options passed to the glm
function.
Value
The function mdscore()
returns the following list of values:
Sr |
the value of the score statistic. |
Srcor |
the value of the modified score statistic. |
coef |
a vector with the coefficients A1 , A2 and A3. |
n |
the total sample size. |
df |
the number of degrees of freedom of the chi–squared approximations for the tests. |
phi |
the precision parameter used in the computations |
Author(s)
Antonio Hermes M. da Silva-Junior hermes@ccet.ufrn.br
Damiao N. da Silva damiao@ccet.ufrn.br
References
Cordeiro GM, Ferrari SLP (1991). A Modified Score Test Statistic Having chi-squared Distribution to Order n–1 . Biometrika, 78(3), 573–582.
Cordeiro GM, Ferrari SLP, Paula GA (1993). Improved Score Tests for Generalized Linear Models. Journal of the Royal Statistical Society B, 55(3), 661–674.
Cribari-Neto F, Ferrari SLP (1995). Second Order Asymptotics for Score Tests in Generalised Linear Models. Biometrika, 82(2), 426–432.
da Silva-Junior AHM, da Silva DN, Ferrari SLP (2014). mdscore: An R Package to Compute Improved Score Tests in Generalized Linear Models. Journal of Statistical Software, 61(2), 1-16., http://www.jstatsoft.org/v61/c02/
See Also
Examples
data(strength)
fitf <- glm(y ~ cut * lot, data = strength,family = inverse.gaussian("inverse"))
summary(fitf)
X <- model.matrix(fitf, data = strength)
fit0 <- glm(y ~ cut + lot, data = strength, family = inverse.gaussian("inverse"))
mdscore(fit0, X1=X[, 7:10])