partsm: Periodic Autoregressive Time Series Models. This package performs basic functions to fit and predict periodic autoregressive time series models. These models are discussed in the book P.H. Franses (1996) ”Periodicity and Stochastic Trends in Economic Time Series”, Oxford University Press. Data set analyzed in that book is also provided. NOTE: the package was orphaned during several years. It is now only maintained, but no major enhancement are expected, and the maintainer cannot provide any support.

References in zbMATH (referenced in 25 articles , 1 standard article )

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  1. Feng, Chunrong; Wu, Yue; Zhao, Huaizhong: Anticipating random periodic solutions. I: SDEs with multiplicative linear noise. (2016)
  2. Ghysels, Eric: Macroeconomics and the reality of mixed frequency data (2016)
  3. Guerbyenne, Hafida; Hamdi, Fayçal: Bootstrapping periodic state-space models (2015)
  4. Liu, Xialu; Cai, Zongwu; Chen, Rong: Functional coefficient seasonal time series models with an application of Hawaii tourism data (2015)
  5. Mohammadpour, M.; Soltani, A.R.: Forward moving average representations for MA processes of finite order: multivariate stationary and periodically correlated (2014)
  6. Pervukhina, Elena; Emmenegger, Jean-Francois; Golikova, Victoria; Osipov, Kostiantyn: An optimization technique based on a vector autoregression model with state space representation: application to Ukrainian cargo transport data (2014)
  7. del Barrio Castro, Tomás; Osborn, Denise R.: Non-parametric testing for seasonally and periodically integrated processes (2012)
  8. Soltani, A.R.; Hashemi, M.: Periodically correlated autoregressive Hilbertian processes (2011)
  9. Bibi, Abdelouahab; Lessak, Radia: On stationarity and $\beta $-mixing of periodic bilinear processes (2009)
  10. Ajmi, Ahdi Noomen; Ben Nasr, Adnen; Boutahar, Mohamed: Seasonal nonlinear long memory model for the US inflation rates (2008)
  11. Castro, Glaysar; Girardin, Valerie: Characterization of periodically correlated and multivariate stationary discrete time wide Markov processes (2008)
  12. Boshnakov, Georgi N.: Multi-companion matrices (2002)
  13. Castro, Glaysar; Girardin, Valerie: Maximum of entropy and extension of covariance matrices for periodically correlated and multivariate processes. (2002)
  14. Ramsay, James O.; Ramsey, James B.: Functional data analysis of the dynamics of the monthly index of nondurable goods production. (2002)
  15. Burridge, Peter; Taylor, A.M.Robert: On regression-based tests for seasonal unit roots in the presence of periodic heteroscedasticity (2001)
  16. Smith, Richard J.; Taylor, A.M.Robert: Recursive and rolling regression-based tests of the seasonal unit root hypothesis (2001)
  17. Koop, Gary; Van Dijk, Hermann K.: Testing for integration using evolving trend and seasonals models: A Bayesian approach. (2000)
  18. Paap, Richard; Franses, Philip Hans: On trends and constants in periodic autoregressions (1999)
  19. Rodrigues, Paulo M.M.; Osborn, Denise R.: Performance of seasonal unit root tests for monthly data (1999)
  20. Kloek, T.: Loss development forecasting models: an econometrician’s view (1998)

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