logLikelihoodMgompertz_UNI

alpha

beta

weight

rcens

weight of the censored observations

rcweight

Tools for homogeneous and in-homogeneous phase-type distributions.
Methods for functional evaluation, simulation and estimation using the
expectation-maximization (EM) algorithm are provided.
The methods of this package are based on the following references.
Asmussen, S., Nerman, O., & Olsson, M. (1996) <https://www.jstor.org/stable/4616418>,
Olsson, M. (1996) <https://www.jstor.org/stable/4616419>.
Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>
Albrecher, H., Bladt, M., & Yslas, J. (2020) <doi:10.1111/sjos.12505>
Bladt, M., & Yslas, J. (2020) <arXiv:2011.03219>.

Martin Bladt

matrixdist

Statistics for Matrix Distributions

Jorge Yslas

logLikelihoodMgompertz_UNI function

<dl><dt>h</dt>
<dd>positive parameter</dd>
<dt>alpha</dt>
<dd>initial probabilities</dd>
<dt>S</dt>
<dd>sub-intensity</dd>
<dt>beta</dt>
<dd>parameter of transformation</dd>
<dt>obs</dt>
<dd>the observations</dd>
<dt>weight</dt>
<dd>weight of the observations</dd>
<dt>rcens</dt>
<dd>censored observations</dd>
<dt>rcweight</dt>
<dd>weight of the censored observations</dd></dl>

Arguments

Loglikelihood of matrix-Gompertz using Uniformization — logLikelihoodMgompertz_UNI

<dl>

<dt>h</dt>
<dd>positive parameter</dd>


<dt>alpha</dt>
<dd>initial probabilities</dd>


<dt>S</dt>
<dd>sub-intensity</dd>


<dt>beta</dt>
<dd>parameter of transformation</dd>


<dt>obs</dt>
<dd>the observations</dd>


<dt>weight</dt>
<dd>weight of the observations</dd>


<dt>rcens</dt>
<dd>censored observations</dd>


<dt>rcweight</dt>
<dd>weight of the censored observations</dd>

</dl>

logLikelihoodMgompertz_UNI: Loglikelihood of matrix-Gompertz using Uniformization

Description

Usage

Arguments