Results 21 to 30 of about 6,276,816 (299)
Empirical Bayes and Full Bayes for Signal Estimation
CoRR, 2014 We consider signals that follow a parametric distribution where the parameter values are unknown. To estimate such signals from noisy measurements in scalar channels, we study the empirical performance of an empirical Bayes (EB) approach and a full Bayes (FB) approach.
Yanting Ma +3 more
openaire +2 more sources
Bayes and Non-Bayes Estimation of Change Point in Nonstandard Mixture Inverse Weibull Distribution
Journal of Statistical Theory and Applications (JSTA), 2019 We consider a sequence of independent random variables X1,X2,…,Xm,…,Xnn≥3 exhibiting a change in the probability distribution of the data generating mechanism.
Masoud Ganji, Roghayeh Mostafayi
doaj +1 more source
An Empirical Bayes Reliability Estimator [PDF]
The Egyptian Statistical Journal, 1980 The reliability function, using exponential life model, is estimated using empirical 'ayes technique. The prior dis-,:ribution which is not assumed known in the empirical Bayes 4pproach, is approximated by Maritz form [3]. The loss func-:ion suggested by
M.R. Abdallah, E.K. El-Hussaini
doaj +1 more source
E-Jurnal Matematika, 2013 Small area is an area with insufficient sample for direct estimation. Limited survey objects, cause direct estimation can not produce better parameter estimates.
PUTU EKA ARIWIJAYANTHI +2 more
doaj +1 more source
Nonparametric Bayes-risk estimation [PDF]
IEEE Transactions on Information Theory, 1971 Two nonparametric methods to estimate the Bayes risk using classified sample sets are described and compared. The first method uses the nearest neighbor error rate as an estimate to bound the Bayes risk. The second method estimates the Bayes decision regions by applying Parzen probability-density function estimates and counts errors made using these ...
Stanley C. Fralick, Richard W. Scott
openaire +1 more source
The systematic risk estimation models: A different perspective
Heliyon, 2020 In practice, the capital asset pricing model (CAPM) using the parametric estimator is almost certainly being used to estimate a firm's systematic risk (beta) and cost of equity as in Eq. (1).
Le Tan Phuoc, Chinh Duc Pham
doaj +1 more source
Reliability Estimation of Weibull -Exponential Distribution via Bayesian Approach
Ratio Mathematica, 2021 Bayesian estimation is employed in order to estimate the reliability function of Weibull-Exponential distribution by using different priors. The Bayes estimators of the reliability function have been obtained under square error, precautionary and entropy
Himanshu Pandey, Arun Kumar Rao
doaj +1 more source
Maximum a posteriori estimators as a limit of Bayes estimators [PDF]
Mathematical Programming, 2018 Maximum a posteriori and Bayes estimators are two common methods of point estimation in Bayesian Statistics. It is commonly accepted that maximum a posteriori estimators are a limiting case of Bayes estimators with 0-1 loss. In this paper, we provide a counterexample which shows that in general this claim is false.
Robert L. Bassett, Julio Deride
openaire +3 more sources
Some results on Bayes estimation under Linex loss function [PDF]
Journal of HyperstructuresIn this paper, we introduced straightforward formulas for the Bayes risk linked to the Linex loss function, which we then applied to estimate parameters of the normal, Poisson, and fractional Weibull distributions.We aimed to investigate the development ...
Masoud Ganji, Fatemeh Gharari
doaj +1 more source
What Are the Odds? A Practical Guide to Computing and Reporting Bayes Factors
Journal of Problem Solving, 2014 The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the Journal of Problem Solving.
A. Jarosz, J. Wiley
semanticscholar +1 more source