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The Use of Fractional Moments for Estimating the Parameters of a Mixed Exponential Distribution

G. M. Tallis, Richard J. Light

Open publisher page 35 citations

Abstract

In this paper the use of fractional moments for estimation purposes is discussed. These ideas are illustrated by means of the mixed exponential distribution. The estimation of the three parameters of the above distribution by the method of moments and by maximum likelihood is investigated numerically in detail. As anticipated, the efficiency of the former method can be greatly increased by using approximately optimal combinations of moments. It is found that the moment method requires only a small amount of calculation when compared with the maximum likelihood method, although charts are presented to greatly ease the computational burden of the latter method.

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What this paper is about

In this paper the use of fractional moments for estimation purposes is discussed. These ideas are illustrated by means of the mixed exponential distribution. The estimation of the three parameters of the above distribution by the method of moments and by maximum likelihood is investigated numerically in detail. As anticipated, the efficiency of the former method can be greatly increased by using approximately optimal combinations of moments. It is found that the moment method requires only a small amount of calculation when compared with the maximum likelihood method, although charts are presented to greatly ease the computational burden of the latter method.

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Available abstract

In this paper the use of fractional moments for estimation purposes is discussed. These ideas are illustrated by means of the mixed exponential distribution. The estimation of the three parameters of the above distribution by the method of moments and by maximum likelihood is investigated numerically in detail. As anticipated, the efficiency of the former method can be greatly increased by using approximately optimal combinations of moments. It is found that the moment method requires only a small amount of calculation when compared with the maximum likelihood method, although charts are presented to greatly ease the computational burden of the latter method.

Key concepts: Mathematics, Natural exponential family, Exponential function, Exponentially modified Gaussian distribution, Exponential distribution, Applied mathematics, Statistics, Distribution (mathematics)

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