CDF_est

This function computes the cumulative distribution function of an univariate distribution (used) in the CVM calculation

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

CDF_est function

<dl><dt>family</dt>
<dd>distribution name; run the command distributions() for help</dd>
<dt>y</dt>
<dd>observations</dd>
<dt>param</dt>
<dd>parameters of the distribution</dd>
<dt>size</dt>
<dd>additional parameter for some discrete distributions</dd>
<dt>u_Ros</dt>
<dd>used internally for the computation of the Rosenblatt transform for non continuous distributions</dd></dl>

Arguments

Cumulative distribution function — CDF_est

<dl>

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


<dt>y</dt>
<dd>observations</dd>


<dt>param</dt>
<dd>parameters of the distribution</dd>


<dt>size</dt>
<dd>additional parameter for some discrete distributions</dd>


<dt>u_Ros</dt>
<dd>used internally for the computation of the Rosenblatt transform for non continuous distributions</dd>

</dl>

CDF_est: Cumulative distribution function

Description

Usage

Value

Arguments