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Minimum message length analysis of multiple short time series

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  • Schmidt, Daniel F.
  • Makalic, Enes

Abstract

This paper applies the Bayesian minimum message length principle to the multiple short time series problem, yielding satisfactory estimates for all model parameters as well as a test for autocorrelation. Connections with the method of conditional likelihood are also discussed.

Suggested Citation

  • Schmidt, Daniel F. & Makalic, Enes, 2016. "Minimum message length analysis of multiple short time series," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 318-328.
    • Handle: RePEc:eee:stapro:v:110:y:2016:i:c:p:318-328
    DOI: 10.1016/j.spl.2015.09.021
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    References listed on IDEAS

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    1. Berger, James O. & Yang, Ruo-Yong, 1994. "Noninformative Priors and Bayesian Testing for the AR(1) Model," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 461-482, August.
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