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Predicting the value of an integer-valued random variable

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  • Jeske, Daniel R.

Abstract

Predicting the value of a random variable Y, based on the observed value of another random variable X is a common objective of data analysis. It is well-known that the minimum mean-squared error predictor of Y is the mean of the conditional distribution of Y, given X. In cases where Y is necessarily integer-valued, the conditional mean is not always a feasible value for Y and, therefore, is an unsatisfactory predicted value. In this paper, it is shown how minimum mean-squared error integer-valued predictors can be obtained.

Suggested Citation

  • Jeske, Daniel R., 1993. "Predicting the value of an integer-valued random variable," Statistics & Probability Letters, Elsevier, vol. 16(4), pages 297-300, March.
    • Handle: RePEc:eee:stapro:v:16:y:1993:i:4:p:297-300
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