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Robust Maximum Likelihood Estimation
INFORMS journal on computing, 2019In many applications, statistical estimators serve to derive conclusions from data, for example, in finance, medical decision making, and clinical trials.
D. Bertsimas, O. Nohadani
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Statistical Inference for Engineers and Data Scientists, 2018
We have learned many different distributions for random variables and all of those distributions had parameters: the numbers that you provide as input when you define a random variable.
E. J. Pitman
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We have learned many different distributions for random variables and all of those distributions had parameters: the numbers that you provide as input when you define a random variable.
E. J. Pitman
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Uncertain maximum likelihood estimation with application to uncertain regression analysis
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020W. Lio, Bao-Ding Liu
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Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
, 1992T. Bollerslev, J. Wooldridge
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Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm
, 1981R. D. Bock, M. Aitkin
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Maximum Likelihood Estimation of Observer ErrorāRates Using the EM Algorithm
, 1979A. Dawid, A. Skene
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Maximum likelihood estimation via the ECM algorithm: A general framework
, 1993Xiao-Li Meng, D. Rubin
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