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Maximum likelihood estimation for ordered expectations of correlated binary variables

机译:相关二元变量的有序期望的最大似然估计

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摘要

A multivariate binary distribution that incorporates the correlation between individual variables is considered. The availability of auxiliary information taking the form of simple ordering constraints on their expected values is assumed. The problem of constructing constraint-preserving estimates for expectations is formulated as conditional maximization of convex likelihood function for corresponding multinomial distribution with suitably chosen restrictions. Starting values for convex optimization algorithms are proposed. The proposed estimator is consistent under mild assumptions.
机译:考虑了包含各个变量之间的相关性的多元二元分布。假定辅助信息的可用性以对它们的期望值的简单排序约束的形式出现。为期望值构造约束保留估计的问题被表达为具有适当选择的约束的相应多项式分布的凸似然函数的条件最大化。提出了凸优化算法的起始值。在温和的假设下,拟议的估计量是一致的。

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