Description Usage Arguments Value Author(s) References See Also Examples
Matrix as a component of modifying part of regression parameters: observed information matrix for fixed number of parameter of interest
1 | infm.weibul(Y, X, sigma, phi, delta, whc)
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Y |
log of Weibull distributed failure times |
X |
covariate matrix |
sigma |
given value of scale parameter of extreme value distribution |
phi |
given values of regression parameters of extreme value distribution |
delta |
Censoring status, coded as 0 (censored observation) and 1 (uncersored observation) binary integer variable |
whc |
Set position of regression parameter of interest corresponding predefined covariate matrix. It will take integer value from 1 to number of regression parameters |
Symmetric matrix of dimension n x n (n is number of regression parameter).
Mazharul Islam and Hasinur Rahaman Khan
Barndorff-Nielsen (1980). Conditionality resolutions. Biometrika, 67(2): 293-310.
Barndorff-Nielsen (1983). On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70(2): 343-365.
Khan M. H. R. and Shaw J. E. H (2016). Variable selection for survival data with a class of adaptive elastic net techniques. Statistics and Computing, 26(3): 725-741.
Islam, M. M., Khan, M. H. R. and Hawlader T. (2015). Modified profile likelihood estimation for the weibull regression models in survival analysis. Submitted.
LX.mat.weibull
1 2 3 4 5 6 7 8 9 10 | dat <- data.weibull(n = 20, shape=2, regco=c(2,1.5,3,2.5))
par=c(1,1,1,1,1,1)
infm.weibul(Y=log(dat$ftime),X=model.matrix(ftime~x1+x2+x3+x4,data=dat),
sigma=2,phi=matrix(par[-1],ncol=1),delta=dat$delta,whc=2)
par=c(1,1,1)
infm.weibul(Y=log(dat$ftime),X=model.matrix(ftime~x1,data=dat),sigma=2,
phi=matrix(par[-1],ncol=1),delta=dat$delta,whc=2)
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