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. . Armillotta, M. and K. Fokianos (2024). "Count network autoregression". Journal of Time Series Analysis, 45(4): 584--612. . 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. .


Reference manual

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install.packages("PNAR")

1.8 by Michail Tsagris, 6 months ago


Browse source code at https://github.com/cran/PNAR


Authors: Michail Tsagris [aut, cre] , Mirko Armillotta [aut, cph] , Konstantinos Fokianos [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports doParallel, foreach, igraph, nloptr, parallel, rangen, Rfast, Rfast2, stats


See at CRAN