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Generalized Autoregressive Moving Average Models


  • Benjamin M.A.
  • Rigby R.A.
  • Stasinopoulos D.M.


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Suggested Citation

  • Benjamin M.A. & Rigby R.A. & Stasinopoulos D.M., 2003. "Generalized Autoregressive Moving Average Models," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 214-223, January.
  • Handle: RePEc:bes:jnlasa:v:98:y:2003:p:214-223

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    Cited by:

    1. Fernando Rojas & Víctor Leiva & Peter Wanke & Camilo Lillo & Jimena Pascual, 2019. "Modeling lot-size with time-dependent demand based on stochastic programming and case study of drug supply in Chile," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-24, March.
    2. Schmidt, Rafael & Schmieder, Christian, 2009. "Modelling dynamic portfolio risk using risk drivers of elliptical processes," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 229-244, April.
    3. Vinicius Q. S. Maior & Francisco José A. Cysneiros, 2018. "SYMARMA: a new dynamic model for temporal data on conditional symmetric distribution," Statistical Papers, Springer, vol. 59(1), pages 75-97, March.
    4. Ella R Rothermel & Matthew T Balazik & Jessica E Best & Matthew W Breece & Dewayne A Fox & Benjamin I Gahagan & Danielle E Haulsee & Amanda L Higgs & Michael H P O’Brien & Matthew J Oliver & Ian A Par, 2020. "Comparative migration ecology of striped bass and Atlantic sturgeon in the US Southern mid-Atlantic bight flyway," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-24, June.
    5. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," NBER Technical Working Papers 0331, National Bureau of Economic Research, Inc.
    6. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    7. Moizes Melo & Airlane Alencar, 2020. "Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 830-857, November.
    8. Song, Peter X.-K. & Freeland, R. Keith & Biswas, Atanu & Zhang, Shulin, 2013. "Statistical analysis of discrete-valued time series using categorical ARMA models," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 112-124.
    9. Klingenberg, Bernhard, 2008. "Regression models for binary time series with gaps," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4076-4090, April.
    10. Tianqing Liu & Xiaohui Yuan, 2013. "Random rounded integer-valued autoregressive conditional heteroskedastic process," Statistical Papers, Springer, vol. 54(3), pages 645-683, August.
    11. E. Andres Houseman & Brent Coull & James Shine, 2004. "A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor," Harvard University Biostatistics Working Paper Series 1017, Berkeley Electronic Press.
    12. Biswas, Atanu & Song, Peter X.-K., 2009. "Discrete-valued ARMA processes," Statistics & Probability Letters, Elsevier, vol. 79(17), pages 1884-1889, September.
    13. Wei-ping Ma & Shuo Gu & Yi Wang & Xian-jing Zhang & Ai-rong Wang & Nai-qing Zhao & Yan-yan Song, 2014. "The Use of Mixed Generalized Additive Modeling to Assess the Effect of Temperature on the Usage of Emergency Electrocardiography Examination among the Elderly in Shanghai," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-10, June.

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