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Estimation of unobserved counts from partially observed multinomial distributions

Author

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  • Sajjan, S. G.
  • Basawa, I. V.

Abstract

The paper is concerned with the problem of estimating (predicting) unobserved counts based on partially observed multinomial panel data from several independent realizations of finite Markov chains. The minimum mean-squared error predictors depend on unknown model parameters which need to be estimated from the same data. The maximum likelihood estimates of the parameters and their limit distributions are derived. The decomposition and approximations of the prediction mean-squared error of the estimated predictors are discussed.

Suggested Citation

  • Sajjan, S. G. & Basawa, I. V., 1997. "Estimation of unobserved counts from partially observed multinomial distributions," Statistics & Probability Letters, Elsevier, vol. 34(3), pages 237-243, June.
    • Handle: RePEc:eee:stapro:v:34:y:1997:i:3:p:237-243
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