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 42 articles , 1 standard article )

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  1. Bauer, Dietmar: Periodic and seasonal (co-)integration in the state space framework (2019)
  2. Mahmoudi, Mohammad Reza; Heydari, Mohammad Hossein; Roohi, Reza: A new method to compare the spectral densities of two independent periodically correlated time series (2019)
  3. Manouchehri, T.; Nematollahi, A. R.: Periodic autoregressive models with closed skew-normal innovations (2019)
  4. Soltani, A. R.; Nematollahi, A. R.; Mahmoudi, M. R.: On the asymptotic distribution of the periodograms for the discrete time harmonizable simple processes (2019)
  5. Boussaha, Nadia; Hamdi, Fayçal: On periodic autoregressive stochastic volatility models: structure and estimation (2018)
  6. Vosseler, Alexander; Weber, Enzo: Forecasting seasonal time series data: a Bayesian model averaging approach (2018)
  7. Mahmoudi, Mohammad Reza; Maleki, Mohsen: A new method to detect periodically correlated structure (2017)
  8. Feng, Chunrong; Wu, Yue; Zhao, Huaizhong: Anticipating random periodic solutions. I: SDEs with multiplicative linear noise. (2016)
  9. Ghysels, Eric: Macroeconomics and the reality of mixed frequency data (2016)
  10. Guerbyenne, Hafida; Hamdi, Fayçal: Bootstrapping periodic state-space models (2015)
  11. Liu, Xialu; Cai, Zongwu; Chen, Rong: Functional coefficient seasonal time series models with an application of Hawaii tourism data (2015)
  12. Mohammadpour, M.; Soltani, A. R.: Forward moving average representations for MA processes of finite order: multivariate stationary and periodically correlated (2014)
  13. 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)
  14. del Barrio Castro, Tomás; Osborn, Denise R.: Non-parametric testing for seasonally and periodically integrated processes (2012)
  15. Soltani, A. R.; Hashemi, M.: Periodically correlated autoregressive Hilbertian processes (2011)
  16. Mouriño, Helena; Barão, Maria Isabel: A comparison between the linear regression model with autocorrelated errors and the partial adjustment model (2010)
  17. Bibi, Abdelouahab; Lessak, Radia: On stationarity and (\beta)-mixing of periodic bilinear processes (2009)
  18. Boshnakov, Georgi N.; Iqelan, Bisher M.: Generation of time series models with given spectral properties (2009)
  19. Ajmi, Ahdi Noomen; Ben Nasr, Adnen; Boutahar, Mohamed: Seasonal nonlinear long memory model for the US inflation rates (2008)
  20. Bentarzi, Mohamed; Guerbyenne, Hafida; Hemis, Roukia: Predictive density order selection of periodic AR models (2008)

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