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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.2 |
rolling source/ R- | GaussianHMM1d_1.1.2.tar.gz |
12.4 KiB |
1.1.2 |
rolling linux/jammy R-4.5 | GaussianHMM1d_1.1.2.tar.gz |
57.0 KiB |
1.1.2 |
latest source/ R- | GaussianHMM1d_1.1.2.tar.gz |
12.4 KiB |
1.1.2 |
latest linux/jammy R-4.5 | GaussianHMM1d_1.1.2.tar.gz |
57.0 KiB |
1.1.2 |
2026-04-23 source/ R- | GaussianHMM1d_1.1.2.tar.gz |
12.4 KiB |
1.1.2 |
2026-04-09 windows/windows R-4.5 | GaussianHMM1d_1.1.2.zip |
64.4 KiB |
1.1.2 |
2025-04-20 source/ R- | GaussianHMM1d_1.1.2.tar.gz |
12.4 KiB |