PNAR: Poisson Network Autoregressive Models
Quasi likelihood-based methods for estimating linear and log-linear Poisson Network Autoregression models with p lags and covariates. Tools for testing the linearity versus several non-linear alternatives. Tools for simulation of multivariate count distributions, from linear and non-linear PNAR models, by using a specific copula construction. References include: Armillotta, M. and K. Fokianos (2022a). Poisson network autoregression. <arXiv:2104.06296>. Armillotta, M. and K. Fokianos (2022b). Testing linearity for network autoregressive models. <arXiv:2202.03852>. Armillotta, M., Tsagris, M. and Fokianos, K. (2022c). The R-package PNAR for modelling count network time series. <arXiv:2211.02582>.
| Version: |
1.5 |
| Depends: |
R (≥ 4.0) |
| Imports: |
doParallel, foreach, igraph, nloptr, parallel, Rfast, Rfast2, stats |
| Published: |
2023-09-15 |
| Author: |
Michail Tsagris [aut, cre],
Mirko Armillotta [aut, cph],
Konstantinos Fokianos [aut] |
| Maintainer: |
Michail Tsagris <mtsagris at uoc.gr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
PNAR results |
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