Results 11 to 20 of about 1,818,807 (197)
Constrained noninformative priors [PDF]
, 1994 The Jeffreys noninformative prior distribution for a single unknown parameter is the distribution corresponding to a uniform distribution in the transformed model where the unknown parameter is approximately a location parameter. To obtain a prior distribution with a specified mean but with diffusion reflecting great uncertainty, a natural ...
Atwood, C. L.
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ANALISIS REGRESI BAYES LINEAR SEDERHANA DENGAN PRIOR NONINFORMATIF [PDF]
E-Jurnal Matematika, 2014 The aim of this study is to apply Bayesian simple linear regression using noninformative prior. The data used in this study is 30 observational data with error generated from normal distribution.
ANAK AGUNG ISTRI AGUNG CANDRA ISWARI +2 more
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Simple Marginally Noninformative Prior Distributions for Covariance Matrices [PDF]
Bayesian Analysis, 2013 A family of prior distributions for covariance matrices is studied. Members of the family possess the attractive property of all standard deviation and correlation parameters being marginally noninformative for particular hyper-parameter choices. Moreover, the family is quite simple and, for approximate Bayesian inference techniques such as Markov ...
Huang, Alan, Wand, M. P.
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On the choice of a noninformative prior for Bayesian inference of discretized normal observations
Computational Statistics, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elster, Clemens, Lira, Ignacio
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Bayesian Approach for Confidence Intervals of Variance on the Normal Distribution
International Journal of Mathematics and Mathematical Sciences, 2022 This research aims to compare estimating the confidence intervals of variance based on the normal distribution with the primary method and the Bayesian approach. The maximum likelihood is the well-known method to approximate variance, and the Chi-squared
Autcha Araveeporn
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Advances in Mathematical Physics, 2022 This paper develops the problem of estimating stress-strength reliability for Gompertz lifetime distribution. First, the maximum likelihood estimation (MLE) and exact and asymptotic confidence intervals for stress-strength reliability are obtained. Then,
Z. Karimi Ezmareh, G. Yari
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Energies, 2022 In this paper, a competing risks model with dependent causes of failure is considered under left-truncated and right-censoring scenario. When the dependent failure causes follow a Marshall–Olkin bivariate exponential distribution, estimation of model ...
Zhiyuan Zuo, Liang Wang, Yuhlong Lio
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A Noninformative Prior for Neural Networks [PDF]
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On the invariance of noninformative priors
The Annals of Statistics, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Datta, Gauri Sankar, Ghosh, Malay
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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
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