Package: PNAR
Type: Package
Title: Poisson Network Autoregressive Models
Version: 1.8
Date: 2026-03-27
Authors@R: c(
           person( "Michail", "Tsagris", role = c("aut", "cre"), email = "mtsagris@uoc.gr" ),
           person( "Mirko", "Armillotta", role = c("aut", "cph"), email = "m.armillotta@vu.nl" ),
           person( "Konstantinos", "Fokianos", role = c("aut"), email = "fokianos@ucy.ac.cy" ) )
Author: Michail Tsagris [aut, cre], Mirko Armillotta [aut, cph],
        Konstantinos Fokianos [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Description: 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 (2023). "Nonlinear network
        autoregression". Annals of Statistics, 51(6): 2526--2552.
        <doi:10.1214/23-AOS2345>. Armillotta, M. and K. Fokianos
        (2024). "Count network autoregression". Journal of Time Series
        Analysis, 45(4): 584--612. <doi:10.1111/jtsa.12728>.
        Armillotta, M., Tsagris, M. and Fokianos, K. (2023). "Inference
        for Network Count Time Series with the R Package PNAR". The R
        Journal, 15/4: 255--269. <doi:10.32614/RJ-2023-094>.
Depends: R (>= 4.0)
Imports: doParallel, foreach, igraph, nloptr, parallel, rangen, Rfast,
        Rfast2, stats
License: GPL (>= 2)
LazyData: true
NeedsCompilation: no
Packaged: 2026-07-04 11:42:56 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2026-03-27 18:07:33 UTC
RemoteUrl: https://github.com/cran/PNAR
RemoteRef: HEAD
RemoteSha: 435ec226a7e45e5c9dd35650e47726ca78e1ae84