Package: GaussianHMM1d 1.1.2
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:
GaussianHMM1d_1.1.2.tar.gz
GaussianHMM1d_1.1.2.zip(r-4.7)GaussianHMM1d_1.1.2.zip(r-4.6)GaussianHMM1d_1.1.2.zip(r-4.5)
GaussianHMM1d_1.1.2.tgz(r-4.6-x86_64)GaussianHMM1d_1.1.2.tgz(r-4.6-arm64)GaussianHMM1d_1.1.2.tgz(r-4.5-x86_64)GaussianHMM1d_1.1.2.tgz(r-4.5-arm64)
GaussianHMM1d_1.1.2.tar.gz(r-4.7-arm64)GaussianHMM1d_1.1.2.tar.gz(r-4.7-x86_64)GaussianHMM1d_1.1.2.tar.gz(r-4.6-arm64)GaussianHMM1d_1.1.2.tar.gz(r-4.6-x86_64)
GaussianHMM1d_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GaussianHMM1d/json (API)
| # Install 'GaussianHMM1d' in R: |
| install.packages('GaussianHMM1d', repos = c('https://bouchranasri.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:d81cfac768. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 131 | ||
| linux-devel-x86_64 | OK | 97 | ||
| source / vignettes | OK | 145 | ||
| linux-release-arm64 | OK | 100 | ||
| linux-release-x86_64 | OK | 94 | ||
| macos-release-arm64 | OK | 82 | ||
| macos-release-x86_64 | OK | 163 | ||
| macos-oldrel-arm64 | OK | 107 | ||
| macos-oldrel-x86_64 | OK | 244 | ||
| windows-devel | OK | 73 | ||
| windows-release | OK | 70 | ||
| windows-oldrel | OK | 75 | ||
| wasm-release | OK | 92 |
Exports:bootstrapfunEstHMM1dEstRegimeForecastHMMetaForecastHMMPdfGaussianMixtureCdfGaussianMixtureInvGaussianMixturePdfGofHMM1dSim.HMM.Gaussian.1dSim.Markov.ChainSimHMMGaussianInvSn
Dependencies:codetoolsdoParallelforeachiterators
