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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 (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>.

Versions across snapshots

VersionRepositoryFileSize
1.8 rolling linux/jammy R-4.5 PNAR_1.8.tar.gz 274.1 KiB
1.8 rolling linux/noble R-4.5 PNAR_1.8.tar.gz 274.1 KiB
1.8 rolling source/ R- PNAR_1.8.tar.gz 65.9 KiB
1.8 latest linux/jammy R-4.5 PNAR_1.8.tar.gz 274.1 KiB
1.8 latest linux/noble R-4.5 PNAR_1.8.tar.gz 274.1 KiB
1.8 latest source/ R- PNAR_1.8.tar.gz 65.9 KiB
1.8 2026-04-26 source/ R- PNAR_1.8.tar.gz 65.9 KiB
1.8 2026-04-23 source/ R- PNAR_1.8.tar.gz 65.9 KiB
1.8 2026-04-09 windows/windows R-4.5 PNAR_1.8.zip 277.0 KiB
1.7 2025-04-20 source/ R- PNAR_1.7.tar.gz 66.1 KiB

Dependencies (latest)

Imports