Publication | Closed Access
New Ways to Prove Central Limit Theorems
164
Citations
7
References
1985
Year
Density EstimationCentral Limit TheoremsEngineeringStatistical FoundationAsymptotic NormalityStatistical InferenceProbability TheoryMathematical StatisticEstimation TheoryStatisticsEmpirical ProcessesRandom Criterion FunctionSemi-nonparametric Estimation
This paper describes some techniques for proving asymptotic normality of statistics defined by maximization of random criterion function. The techniques are based on a combination of recent results from the theory of empirical processes and a method of Huber for the study of maximum likelihood estimators under nonstandard conditions.
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