R: Summarizing fits from Stochastic EM algorithm for...

summary.spRMM {mixtools} | R Documentation

## Summarizing fits from Stochastic EM algorithm for semiparametric scaled mixture of censored data

### Description

`summary` method for class `spRMM`.

### Usage

    ## S3 method for class 'spRMM'
    summary(object, digits = 6, ...)

### Arguments

`object` | an object of class `spRMM` such as a result of a call to `spRMM_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.

### Author(s)

Didier Chauveau

### 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. http://link.springer.com/article/10.1007/s00180-016-0661-7

### 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`.

### Examples

    # See example(spRMM_SEM)

[Package mixtools version 1.2.0 Index]