Results 11 to 20 of about 832,071 (345)
The Comparison Between the Bayes Estimator and the Maximum Likelihood Estimator of the Reliability Function for Negative Exponential Distribution [PDF]
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2018 In this paper, the maximum likelihood estimator and the Bayes estimator of the reliability function for negative exponential distribution has been derived, then a Monte –Carlo simulation technique was employed to compare the performance of such ...
Hazim Mansour Gorgees +2 more
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Asymptotic behaviour of the empirical Bayes posteriors associated to maximum marginal likelihood estimator [PDF]
, 2015 We consider the asymptotic behaviour of the marginal maximum likelihood empirical Bayes posterior distribution in general setting. First we characterize the set where the maximum marginal likelihood estimator is located with high probability.
J. Rousseau, Botond Szabó
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LARGE DEVIATION PROBABILITIES FOR MAXIMUM LIKELIHOOD ESTIMATOR AND BAYES ESTIMATOR OF A PARAMETER FOR FRACTIONAL ORNSTEIN-UHLENBECK TYPE PROCESS [PDF]
, 2006 We investigate the probabilities of large deviations of the maximum likelihood estimator and Bayes estimator of the drift parameter for a fractional Ornstein-Uhlenbeck type ...
M. N. Mishra, B. Rao
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Bayes-Optimal Unsupervised Learning for Channel Estimation in Near-Field Holographic MIMO [PDF]
IEEE Journal on Selected Topics in Signal Processing, 2023 Holographic MIMO (HMIMO) is being increasingly recognized as a key enabling technology for 6G wireless systems through the deployment of an extremely large number of antennas within a compact space to fully exploit the potentials of the electromagnetic ...
Wentao Yu +6 more
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IEEE Access, 2020 Mixture modelling has stunning applications to explain the composite problems in simple way. Bayesian demonstration of 3-Component mixture model of Exponentiated Pareto distribution in right-type-I censoring scheme is presented in this article.
Ammara Nawaz Cheema +3 more
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Bayesian Inference for the Loss Models via Mixture Priors
Risks, 2023 Constructing an accurate model for insurance losses is a challenging task. Researchers have developed various methods to model insurance losses, such as composite models. Composite models combine two distributions: one for part of the data with small and
Min Deng, Mostafa S. Aminzadeh
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Multivariate, heteroscedastic empirical Bayes via nonparametric maximum likelihood [PDF]
Journal of The Royal Statistical Society Series B-statistical Methodology, 2021 Multivariate, heteroscedastic errors complicate statistical inference in many large-scale denoizing problems. Empirical Bayes is attractive in such settings, but standard parametric approaches rest on assumptions about the form of the prior ...
J. Soloff +2 more
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Journal of Statistical Theory and Applications (JSTA), 2018 This paper studies the Bayes estimator, the maximum likelihood estimator and the approximate likelihood estimator of the scale parameter for the Marshall-Olkin exponential distribution under the progressive type-II censored sample.
Mukhtar M. Salah
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The Annals of Mathematical Statistics, 1967 Throughout this paper we are concerned with the problem of estimating a real parameter when the loss function is such that the Bayes estimate exists, is unique, and satisfies a simple Equation, (1.5). If the estimate is unbiased (in the general sense of Lehmann [3]) we show under weak conditions that it must satisfy another Equation, (1.14).
Bickel, Peter J., Blackwell, David
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On the Consistency of Bayes Estimates
The Annals of Statistics, 1986 The authors of this special invited paper give the following summary: ''We discuss frequency properties of Bayes rules, paying special attention to consistency. Some new and fairly natural counterexamples are given, involving nonparametric estimates of location.
Diaconis, Persi, Freedman, David
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