Choosing the smoothing parameter for unordered multinormal data

Jones, M. C. and Vines, S. K. (1998). Choosing the smoothing parameter for unordered multinormal data. TEST, 7(2) pp. 413–426.

DOI: https://doi.org/10.1007/BF02565121

Abstract

We consider the estimation of multinomial probabilities in the non-sparse univariate unordered case. We describe a number of explicit methods (mostly pre-existing) for the choice of the smoothing parameter in this context. In simulations, we compare these methods in terms of mean root mean squared error performance. Our recommendation is for the routine use of the simplest Bayesian estimation formula in which the probability in the k'th cell is estimated by (nk +1)/(N+K) where nk is the count in the k'th cell, N is the sample size and K is the number of cells.

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