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Time Series Models for Count or Qualitative Observations

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Author Info
Harvey, Andrew C
Fernandes, C

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Abstract

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Publisher Info
Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 7 (1989)
Issue (Month): 4 (October)
Pages: 407-17
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Handle: RePEc:bes:jnlbes:v:7:y:1989:i:4:p:407-17

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  1. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  2. J. Keith Ord & Rob J. Hyndman & Anne B. Koehler & Ralph D. Snyder, 2008. "Monitoring Processes with Changing Variances," Monash Econometrics and Business Statistics Working Papers 4/08, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  3. HEINEN, AndrŽas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," CORE Discussion Papers 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
    Other versions:
  4. Christian Gourieroux & Joann Jasiak, 2001. "Dynamic Factor Models," Econometric Reviews, Taylor and Francis Journals, vol. 20(4), pages 385-424. [Downloadable!] (restricted)
  5. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," CORE Discussion Papers 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
  6. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
Statistics
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This page was last updated on 2009-11-22.


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