rwrpcauchy

Sample from wrapped Cauchy distribution

Fitting hidden Markov models using automatic differentiation
and Laplace approximation, allowing for fast inference and flexible covariate
effects (including random effects and smoothing splines) on model parameters.
The package is described by Michelot (2022) <doi:10.48550/arXiv.2211.14139>.

Theo Michelot

hmmTMB

Fit Hidden Markov Models using Template Model Builder

Richard Glennie

rwrpcauchy function

<dl><dt>n</dt>
<dd>Number of samples</dd>
<dt>mu</dt>
<dd>Mean parameter</dd>
<dt>rho</dt>
<dd>Concentration parameter</dd></dl>

Arguments

Sample from wrapped Cauchy distribution — rwrpcauchy

<dl>

<dt>n</dt>
<dd>Number of samples</dd>


<dt>mu</dt>
<dd>Mean parameter</dd>


<dt>rho</dt>
<dd>Concentration parameter</dd>

</dl>

rwrpcauchy: Sample from wrapped Cauchy distribution

Description

Usage

Value

Arguments

Details