The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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. (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>.

Version: 1.7
Depends: R (≥ 4.0)
Imports: doParallel, foreach, igraph, nloptr, parallel, Rfast, Rfast2, stats
Published: 2024-09-05
DOI: 10.32614/CRAN.package.PNAR
Author: Michail Tsagris [aut, cre], Mirko Armillotta [aut, cph], Konstantinos Fokianos [aut]
Maintainer: Michail Tsagris <mtsagris at uoc.gr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: PNAR results

Documentation:

Reference manual: PNAR.pdf

Downloads:

Package source: PNAR_1.7.tar.gz
Windows binaries: r-devel: PNAR_1.7.zip, r-release: PNAR_1.7.zip, r-oldrel: PNAR_1.7.zip
macOS binaries: r-release (arm64): PNAR_1.7.tgz, r-oldrel (arm64): PNAR_1.7.tgz, r-release (x86_64): PNAR_1.7.tgz, r-oldrel (x86_64): PNAR_1.7.tgz
Old sources: PNAR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PNAR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.