Summarizing fits from Stochastic EM algorithm for semiparametric scaled mixture of censored data
summary.spRMM.Rdsummary method for class spRMM.
Usage
# S3 method for class 'spRMM'
summary(object, digits = 6, ...)Arguments
- object
an object of class
spRMMsuch as a result of a call tospRMM_SEM- digits
Significant digits for printing values
- ...
Additional parameters passed to
print.
Details
summary.spRMM prints scalar parameter estimates for
a fitted mixture model: each component weight and the scaling factor, see reference below.
The functional (nonparametric) estimates of survival and hazard rate funcions can be obtained
using plotspRMM.
Value
The function summary.spRMM prints the final loglikelihood
value at the solution as well as The estimated mixing weights and the scaling parameter.
See also
Function for plotting functional (nonparametric) estimates:
plotspRMM.
Other models and algorithms for censored lifetime data
(name convention is model_algorithm):
expRMM_EM,
weibullRMM_SEM.
References
Bordes, L., and Chauveau, D. (2016), Stochastic EM algorithms for parametric and semiparametric mixture models for right-censored lifetime data, Computational Statistics, Volume 31, Issue 4, pages 1513-1538. https://link.springer.com/article/10.1007/s00180-016-0661-7