Updating a nonlinear discriminant function estimated from a mixture of two Weibull distributions
โ 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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โฆ 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.
๐ SIMILAR VOLUMES
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