ZINB.GP
Bayesian Zero-Inflated Negative Binomial Gaussian Process Models
Fits Bayesian zero-inflated negative binomial regression models with Gaussian process random effects for spatial, temporal, or spatiotemporal count data. Provides Markov chain Monte Carlo sampling, configurable random effects in the zero-inflation and count components, and posterior predictive draws. Implements a full GP version of the methods described by He and Huang (2024) <doi:10.1016/j.jspi.2023.106098>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | ZINB.GP_1.0.0.tar.gz |
1.7 MiB |
1.0.0 |
rolling linux/noble R-4.5 | ZINB.GP_1.0.0.tar.gz |
1.7 MiB |
1.0.0 |
rolling source/ R- | ZINB.GP_1.0.0.tar.gz |
1.6 MiB |
1.0.0 |
latest linux/jammy R-4.5 | ZINB.GP_1.0.0.tar.gz |
1.7 MiB |
1.0.0 |
latest linux/noble R-4.5 | ZINB.GP_1.0.0.tar.gz |
1.7 MiB |
1.0.0 |
latest source/ R- | ZINB.GP_1.0.0.tar.gz |
1.6 MiB |
1.0.0 |
2026-04-23 source/ R- | ZINB.GP_1.0.0.tar.gz |
0 B |