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Abstract New techniques of local sensitivity analysis for nonsmooth generalized equations are applied to the study of sequences of statistical estimates 




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Asymptotic Minimax Theory Alexander Korostelev As a function of ?, this joint probability has the algebraic form of a gamma The solution is c = 0

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In §1 2 we review basic results from probability theory on different modes of convergence relevant to sequences of random variables and random vectors, and then 

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King, A J and Rockafellar, R T (1990) Asymptotic Theory for Solutions in Many problem formulations in statistics and stochastic optimization generate 




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Asymptotic Theory of Statistical Estimation 1 Jiantao Jiao The maximum likelihood estimator ˆ?n is the solution of the equation

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INSTRUCTOR'S SOLUTIONS MANUAL (ONLINE ONLY) MARK SCHERVISH Carnegie Mellon University PROBABILITY AND STATISTICS FOURTH EDITION Morris DeGroot

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ASYMPTOTIC THEORY FOR SOLUTIONS IN STATISTICAL ESTIMATION AND STOCHASTIC PROGRAMMING Alan J King† and R Tyrrell Rockafellar‡

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where Cn = Cn(X1, ,Xn) is the normalizing constant independent of θ As a function of θ, this joint probability has the algebraic form of a gamma distribution

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2 6 Asymptotic normality for functions of random variables 24 2 7 Sum experimental setup is redundant in the probability theory In fact, we do distribution for statistical inference Suppose that ξp is the unique solution of F( x−) ≤

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