估计员
数学
趋同(经济学)
平滑度
应用数学
最大化
序列(生物学)
期望最大化算法
数学优化
最大似然
统计
数学分析
经济增长
遗传学
生物
经济
作者
Andreas Andresen,Vladimir Spokoiny
摘要
We derive two convergence results for a sequential alternating maximization procedure to approximate the maximizer of random functionals such as the realized log likelihood in MLE estimation. We manage to show that the sequence attains the same deviation properties as shown for the profile M-estimator by Andresen and Spokoiny (2013), that means a finite sample Wilks and Fisher theorem. Further under slightly stronger smoothness constraints on the random functional we can show nearly linear convergence to the global maximizer if the starting point for the procedure is well chosen.
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