GaussianHMM1d: Inference, Goodness-of-Fit and Forecast for Univariate Gaussian Hidden Markov Models

Inference, goodness-of-fit test, and prediction densities and intervals for univariate Gaussian Hidden Markov Models (HMM). The goodness-of-fit 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 Chapter 10.2 of Remillard (2013) <doi:10.1201/b14285>.

Getting started

Package details

AuthorBouchra R. Nasri and Bruno N. Remillard
MaintainerBouchra Nasri <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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GaussianHMM1d documentation built on May 1, 2019, 9:22 p.m.