GenHMM1d
Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov Models
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) <doi:10.1029/2019WR025122>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.6 |
rolling source/ R- | GenHMM1d_0.2.6.tar.gz |
43.2 KiB |
0.2.6 |
rolling linux/jammy R-4.5 | GenHMM1d_0.2.6.tar.gz |
258.5 KiB |
0.2.6 |
latest source/ R- | GenHMM1d_0.2.6.tar.gz |
43.2 KiB |
0.2.6 |
latest linux/jammy R-4.5 | GenHMM1d_0.2.6.tar.gz |
258.5 KiB |
0.2.6 |
2026-04-23 source/ R- | GenHMM1d_0.2.6.tar.gz |
43.2 KiB |
0.2.6 |
2026-04-09 windows/windows R-4.5 | GenHMM1d_0.2.6.zip |
261.4 KiB |
0.2.1 |
2025-04-20 source/ R- | GenHMM1d_0.2.1.tar.gz |
43.0 KiB |