Summarizing fits from Stochastic EM algorithm for semiparametric scaled mixture of censored data
summary method for class spRMM.
## S3 method for class 'spRMM' summary(object, digits = 6, ...)
object |
an object of class |
digits |
Significant digits for printing values |
... |
Additional parameters passed to |
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.
The function summary.spRMM prints the final loglikelihood
value at the solution as well as The estimated mixing weights and the scaling parameter.
Didier Chauveau
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. http://link.springer.com/article/10.1007/s00180-016-0661-7
Function for plotting functional (nonparametric) estimates:
plotspRMM.
Other models and algorithms for censored lifetime data
(name convention is model_algorithm):
expRMM_EM,
weibullRMM_SEM.
# See example(spRMM_SEM)
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