Estimating density functions: a constrained maximum likelihood approach
Estimating density functions: a constrained maximum likelihood approach
复制标题
估计密度函数：约束最大似然方法
DOI：
10.1080/10485250008832822
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发表时间：
2000
影响因子：
1.2
通讯作者：
R. Wets
中科院分区：
文献类型：
--
作者：
Michael X. Dong;R. Wets
我们建议通过一个约束优化问题来估计密度函数，该约束优化问题的准则函数是最大似然函数，其约束模型是任何(先验)可用的信息。这种方法的渐近正当性依赖于表观收敛理论。一个简单的数值例子被用来表明这种方法的潜力。
We propose estimating density functions by means of a constrained optimization problem whose criterion function is the maximum likelihood function, and whose constraints model any (prior) information that might be available. The asymptotic justification for such an approach relies on the theory of epi-convergence. A simple numerical example is used to signal the potential of such an approach.