Results 41 to 50 of about 2,617,552 (333)
Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector [PDF]
, 2013 For the important classical problem of inference on a sparse high-dimensional normal mean vector, we propose a novel empirical Bayes model that admits a posterior distribution with desirable properties under mild conditions.
Ryan Martin, S. Walker
semanticscholar +1 more source
AIMS Mathematics, 2022 In this article, reliability estimation for a system of multi-component stress-strength model is considered. Working under progressively censored samples is of great advantage over complete and usual censoring samples, therefore Type-II right progressive
Hanan Haj Ahmad +2 more
doaj +1 more source
Jurnal Matematika UNAND, 2019 Penelitian ini bertujuan untuk menduga angka pengangguran di kabupaten/kota di Sumatea Barat dengan metode Small Area Estimation dengan pendekatan Empirical Bayes berbasis model Beta-Binomial.
Nurmaylina Zaja +2 more
doaj +1 more source
Bayes and empirical bayes estimation of parameter K in negative binomial distribution [PDF]
Journal of Hyperstructures, 2013 In this paper, the problem of estimating the number of successes, k, in a negative binomial distribution for both known and unknown probability p of success are examined by a Bayesian point of view. Also, we introduce two estimations for the parameter of
Masoud Ganji +2 more
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The Annals of Statistics, 1978 Let $x_1, \cdots, x_n$ be i.i.d. random variables with a distribution depending on the real parameter. Under what conditions is a generalized Bayes estimator independent of the choice of the even loss function? The known answer to this question is that this independence holds if the posterior density is symmetric and unimodal.
openaire +3 more sources
Bayes Estimation for Inverse Rayleigh Model under Different Loss Functions
, 2015 The inverse Rayleigh distribution plays an important role in life test and reliability domain. The aim of this article is study the Bayes estimation of parameter of inverse Rayleigh distribution.
Guobing Fan
semanticscholar +1 more source
Consistency of variational Bayes inference for estimation and model selection in mixtures [PDF]
, 2018 Mixture models are widely used in Bayesian statistics and machine learning, in particular in computational biology, natural language processing and many other fields.
Badr-Eddine Ch'erief-Abdellatif +1 more
semanticscholar +1 more source
A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution
MathematicsBayes minimax estimation is important because it provides a robust approach to statistical estimation that considers the worst-case scenario while incorporating prior knowledge.
Shokofeh Zinodiny, Saralees Nadarajah
doaj +1 more source
Austrian Journal of Statistics, 2015 This paper derives Bayes shrinkage estimator of Rayleigh parameter and its associated risk based on conjugate prior under the assumption of general entropy loss function for progressive type-II censored data. Risk function of maximum likelihood estimate,
Sanku Dey +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background We describe clinical and biologic characteristics of neuroblastoma in older children, adolescents, and young adults (OCAYA); describe survival outcomes in the post‐immunotherapy era; and identify if there is an age cut‐off that best discriminates outcomes.
Rebecca J. Deyell +14 more
wiley +1 more source