theta2alpha

This function computes the unconstrained parameters alpha of a univariate distribution corresponding to constrained parameters theta.

internal

Inference, goodness-of-fit tests, and predictions for continuous and discrete univariate Hidden Markov Models (HMM), including zero-inflated distributions. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Nasri et al (2020) <doi:10.1029/2019WR025122>.

Bouchra Nasri

GenHMM1d

Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov
Models

Mamadou Yamar Thioub

theta2alpha function

<dl><dt>family</dt>
<dd>distribution name; run the command distributions() for help</dd>
<dt>theta</dt>
<dd>constrained parameters of the univariate distribution</dd></dl>

Arguments

Transform constrained parameters to unconstrained parameters — theta2alpha

<dl>

<dt>family</dt>
<dd>distribution name; run the command distributions() for help</dd>


<dt>theta</dt>
<dd>constrained parameters of the univariate distribution</dd>

</dl>

theta2alpha: Transform constrained parameters to unconstrained parameters

Description

Usage

Value

Arguments