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PNAR

Poisson Network Autoregressive Models

v1.7 · Sep 5, 2024 · GPL (>= 2)

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. (2024). "Inference for Network Count Time Series with the R Package PNAR". The R Journal, 15/4: 255--269. <doi:10.32614/RJ-2023-094>.

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package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
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ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 9, 2026
ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.

Dependency Network

Dependencies Reverse dependencies doParallel foreach igraph nloptr Rfast Rfast2 PNAR

Version History

new 1.7 Mar 9, 2026