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Estimation by Maximum Entropy Subject to Second-Order Conditions

✍ Scribed by L. P. Lefkovitch

Publisher
John Wiley and Sons
Year
1989
Tongue
English
Weight
961 KB
Volume
31
Category
Article
ISSN
0323-3847

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✦ Synopsis

If the variance, V = V(p, S) is some known function of the mean, ,u=p(&, where and may include unknown parameters, then given empirical data, this paper describes how to es?;imate the unknown parameters by choosing them to satisfy the variance/mean relationship, and simultaneously to require that the sampling probability distribution haa maximum entropy. Bounds for the estimated values of the unknown parameters can be obtained by a further application of the maximum entropy principle. The p,wer variance function, V(p) =Ape is discussed, including some special came of , I and 6. The procedure is briefly compared with quasi-likelihood, and illustrated by some numerical examples.

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