alpha2theta

This function computes the constrained parameters theta of a univariate distribution, from the unconstrained parameter alpha.

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

alpha2theta function

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

Arguments

Transformation of unconstrained parameters to constrained  parameters — alpha2theta

<dl>

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


<dt>alpha</dt>
<dd>unconstrained parameters of the univariate distribution</dd>

</dl>

alpha2theta: Transformation of unconstrained parameters to constrained parameters

Description

Usage

Value

Arguments