Iterative numerical methods are necessary t o find the maximum likelihood estimates for finite mixture distributions. This paper shows that it will often be possible to analytitally reduce the number of equations that must ultimately be solved numerically. Such a reduction in dimensionality has not
โฆ LIBER โฆ
Maximum likelihood estimation under a finite mixture of generalized exponential distributions based on censored data
โ Scribed by Saieed F. Ateya
- Book ID
- 120787240
- Publisher
- Springer-Verlag
- Year
- 2012
- Tongue
- English
- Weight
- 391 KB
- Volume
- 55
- Category
- Article
- ISSN
- 0932-5026
No coin nor oath required. For personal study only.
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This article derives the asymptotic results of the maximum-likelihood estimates of the parameters in the general bivariate continuous distribution for the data type, in which the failure time and the censoring variables are dependent. This data type is motivated from life-testing two-component paral