Package: GaussianHMM1d 1.1.1

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>.

Authors:Bouchra R. Nasri [aut, cre, cph], Bruno N Remillard [aut, ctb, cph]

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GaussianHMM1d/json (API)

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13 exports 0.09 score 4 dependencies 12 scripts 187 downloads

Last updated 1 years agofrom:91d43c8da6. Checks:OK: 4 NOTE: 5. Indexed: yes.

Exports:bootstrapfunEstHMM1dEstRegimeForecastHMMetaForecastHMMPdfGaussianMixtureCdfGaussianMixtureInvGaussianMixturePdfGofHMM1dSim.HMM.Gaussian.1dSim.Markov.ChainSimHMMGaussianInvSn

Dependencies:codetoolsdoParallelforeachiterators