msBIC {mixPHM} | R Documentation |
This function fits models for different proportionality restrictions.
msBIC(x, K, method = "all", Sdist = "weibull", cutpoint = NULL, EMoption = "classification", EMstop = 0.01, maxiter = 100)
x |
Data frame or matrix of dimension n*p with survival times (NA 's allowed). |
K |
A vector with number of mixture components. |
method |
A vector with the methods provided in phmclust :
With "separate" no restrictions are imposed, "main.g" relates to a group main effect,
"main.p" to the variables main effects. "main.gp" reflects the proportionality assumption over groups
and variables. "int.gp" allows for interactions between groups and variables. If method is "all" , each model is fitted. |
Sdist |
Various survival distrubtions such as "weibull" , "exponential" , and "rayleigh" . |
cutpoint |
Cutpoint for censoring |
EMoption |
"classification" is based on deterministic cluster assignment,
"maximization" on deterministic assignment, and "randomization"
provides a posterior-based randomized cluster assignement. |
EMstop |
Stopping criterion for EM-iteration. |
maxiter |
Maximum number of iterations. |
Based on the output BIC matrix, model selection can be performed in terms of the number of mixture components and imposed proportionality restrictions.
Returns an object of class BICmat
with the following values:
BICmat |
Matrix with BIC values |
K |
Vector with different components |
method |
Vector with proportional hazard methods |
Sdist |
Survival distribution |
##Fitting 3 Weibull proportional hazard models (over groups, pages) for K=2,3 components data(webshop) res <- msBIC(webshop, K = c(2,3), method = c("main.p","main.g"), maxiter = 10) res