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GenHMM1d (version 0.2.1)

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

Description

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) .

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Version

Install

install.packages('GenHMM1d')

Monthly Downloads

10,780

Version

0.2.1

License

GPL-3

Maintainer

Bouchra Nasri

Last Published

March 13th, 2025

Functions in GenHMM1d (0.2.1)

alpha2theta

Transformation of unconstrained parameters to constrained parameters
ForecastHMMVAR

Value at risk (VAR) of a univariate HMM at time n+k1, n+k2, ...
distributions

The names and descriptions of the univariate distributions
ForecastHMMeta

Predicted probabilities of regimes of a univariate HMM for a new observation
bfun

Bootstrap for the univariate distributions
PDF

Probability density function
CDF

Cumulative distribution function
PDF_unc

Probability density function
CDF_est

Cumulative distribution function
graphEstim

Graphs
theta2alpha

Transform constrained parameters to unconstrained parameters
SimMarkovChain

Markov chain simulation
QUANTILE

Quantile function
SimHMMGen

Simulation of univariate hidden Markov model
Snd1

Cramer-von Mises statistic for the goodness-of-fit test of the null hypothesis of a univariate uniform distribution over [0,1]
ES

Expected shortfall function
GofHMMGen

Goodness-of-fit of univariate hidden Markov model
GridSearchS0

Gridsearch
ForecastHMMPdf

Forecasted density function of a univariate HMM at time n+k1, n+k2, ...
ForecastHMMCdf

Forecasted cumulative distribution function of a univariate HMM at times n+k1, n+k2,....
EstHMMGen

Estimation of univariate hidden Markov model