truncfactorial

truncated factorial to avoid stack overflow for huge values

models

methods

Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, which allow for estimating posterior model probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.

Waldir Leoncio

EMJMCMC

Evolutionary Mode Jumping Markov Chain Monte Carlo Expert
Toolbox

Aliaksandr Hubin

Geir Storvik

Florian Frommlet

truncfactorial function

<dl><dt>x</dt>
<dd>a non-negative integer number</dd></dl>

Arguments

Truncated factorial to avoid stack overflow for huge values — truncfactorial

<dl>

<dt>x</dt>
<dd>a non-negative integer number</dd>

</dl>

truncfactorial: Truncated factorial to avoid stack overflow for huge values

Description

Usage

Value

Arguments

Examples