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. <doi:10.48550/arXiv.2104.06296>. Armillotta, M. and K. Fokianos (2022b). Testing linearity for network autoregressive models. <doi:10.48550/arXiv.2202.03852>. Armillotta, M., Tsagris, M. and Fokianos, K. (2022c). The R-package PNAR for modelling count network time series. <doi:10.48550/arXiv.2211.02582>.

Version: 1.6
Depends: R (≥ 4.0)
Imports: doParallel, foreach, igraph, nloptr, parallel, Rfast, Rfast2, stats
Published: 2023-10-09
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

Documentation:

Reference manual: PNAR.pdf

Downloads:

Package source: PNAR_1.6.tar.gz
Windows binaries: r-devel: PNAR_1.6.zip, r-release: PNAR_1.6.zip, r-oldrel: PNAR_1.6.zip
macOS binaries: r-release (arm64): PNAR_1.6.tgz, r-oldrel (arm64): PNAR_1.6.tgz, r-release (x86_64): PNAR_1.6.tgz
Old sources: PNAR archive

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