Package: PNAR 1.6
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Michail Tsagris
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 (2022a). Poisson network autoregression. <arxiv:2104.06296>. Armillotta, M. and K. Fokianos (2022b). Testing linearity for network autoregressive models. <arxiv:2202.03852>. Armillotta, M., Tsagris, M. and Fokianos, K. (2022c). The R-package PNAR for modelling count network time series. <arxiv:2211.02582>.
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PNAR_1.6.tar.gz
PNAR_1.6.tar.gz(r-4.5-noble)PNAR_1.6.tar.gz(r-4.4-noble)
PNAR_1.6.tgz(r-4.4-emscripten)PNAR_1.6.tgz(r-4.3-emscripten)
PNAR.pdf |PNAR.html✨
PNAR/json (API)
# Install 'PNAR' in R: |
install.packages('PNAR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:f5a6f0fc3b
Exports:adjaadja_gnpgetNglobal_optimise_LM_stnarpqglobal_optimise_LM_tnarpqlin_estimnarpqlin_ic_plotlin_narpq_initlog_lin_estimnarpqlog_lin_ic_plotlog_lin_narpq_initpoisson.MODpqpoisson.MODpq.logpoisson.MODpq.nonlinpoisson.MODpq.stnarpoisson.MODpq.tnarrcopulascore_test_nonlinpq_h0score_test_stnarpq_DVscore_test_stnarpq_jscore_test_tnarpq_j
Dependencies:clicodetoolscpp11doParallelforeachglueigraphiteratorslatticelifecyclemagrittrMatrixnloptrpkgconfigRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratRfastRfast2rlangRnanoflannvctrs