On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size
In: Journal of statistical computation and simulation (Print), Jg. 73 (2003), Heft 12, S. 867-886
academicJournal
- print, 1 p.1/4
Zugriff:
The property of identifiability is an important consideration on estimating the parameters in a mixture of distributions. Also classification of a random variable based on a mixture can be meaning fully discussed only if the class of all finite mixtures is identifiable. The problem of identifiability of finite mixture of Gompertz distributions is studied. A procedure is presented for finding maximum likelihood estimates of the parameters of a mixture of two Gompertz distributions, using classified and unclassified observations. Based on small sample size, estimation of a nonlinear discriminant function is considered. Throughout simulation experiments, the performance of the corresponding estimated nonlinear discriminant function is investigated.
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On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size
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Autor/in / Beteiligte Person: | MOUSTAFA, H. M ; RAMADAN, S. G |
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Zeitschrift: | Journal of statistical computation and simulation (Print), Jg. 73 (2003), Heft 12, S. 867-886 |
Veröffentlichung: | Abingdon: Taylor and Francis, 2003 |
Medientyp: | academicJournal |
Umfang: | print, 1 p.1/4 |
ISSN: | 0094-9655 (print) |
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