On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size
On MLE of a nonlinear discriminant function from a mixture of two Gompertz distributions based on small sample size
复制标题
基于小样本量的两个 Gompertz 分布混合非线性判别函数的 MLE
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
S. Ramadan
中科院分区：
文献类型：
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作者：
H. M. Moustafa;S. Ramadan
可辨识性是估计混合分布参数的一个重要考虑因素。此外，只有当所有有限混合物的类是可识别的时，基于混合物的随机变量的分类才能被充分讨论。研究了Gompertz分布的有限混合的可识别性问题。一个程序，用于寻找两个Gompertz分布的混合物的参数的最大似然估计，使用分类和未分类的观察。在小样本条件下，研究了非线性判别函数的估计问题。在整个仿真实验中，相应的估计的非线性判别函数的性能进行了研究。
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.