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Updating a nonlinear discriminant function estimated from a mixture of two Weibull distributions

โœ Scribed by K.E. Ahmad; A.M. Abd-Elrahman


Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
837 KB
Volume
19
Category
Article
ISSN
0895-7177

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โœฆ Synopsis


procedure is presented for finding maximum likelihood estimates of the parameters of a mixture of two Weibull distributions. Estimation of a nonlinear discriminant function on the basis of small sample size is considered. Throughout simulation experiments, the total probabilities of misclassification and percentage biases are evaluated and discussed. The problem of updating a nonlinear discriminant function on the basis of two Weibull distributions is studied in situations when the additional observations are mixed or classified. The performance of all results is investigated using a series of simulation experiments by means of relative efficiencies.


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A procedure is presented for finding maximum likelihood estimates of the parameters of a mixture of two gamma distributions; those results are given for classified and unclassified observations. The performance of the estimates based on small samples is studied by simulation experiments. Estimation