Poisson Network Autoregressive Models R package PNAR version 1.8 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>. Software Depends: R (>= 4.0) Imports: doParallel, foreach, igraph, nloptr, parallel, rangen, Rfast, Rfast2, stats Michail Tsagris <mtsagris@uoc.gr> Comprehensive R Archive Network (CRAN) Michail Tsagris [aut, cre], Mirko Armillotta [aut, cph], Konstantinos Fokianos [aut] GPL (>= 2) 2026-03-27 application/tgz https://CRAN.R-project.org/package=PNAR doi:10.32614/CRAN.package.PNAR