Results 31 to 40 of about 212,322 (298)

Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors

مجلة بغداد للعلوم, 2013
In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two ...
Baghdad Science Journal
doaj   +1 more source

Bayes Estimators of Exponential Parameters from a Censored Sample Using a Guessed Estimate

Data Science Journal, 2008
This paper provides the Bayes estimators of the failure rate and reliability function for a one-parameter, exponential distribution by utilizing a point guess estimate of the parameter.
G P Singh, S K Singh, Umesh Singh, S K Upadhyay   +3 more
doaj   +1 more source

Bayesian estimation for Dagum distribution based on progressive type I interval censoring.

PLoS ONE, 2021
In this paper, we consider Dagum distribution which is capable of modeling various shapes of failure rates and aging criteria. Based on progressively type-I interval censoring data, we first obtain the maximum likelihood estimators and the approximate ...
Refah Alotaibi, Hoda Rezk, Sanku Dey, Hassan Okasha   +3 more
doaj   +1 more source

Bayesian Estimation of R= P [ y < X ] for Burr Type XII Distribution Using Extreme Ranked Set Sampling [PDF]

The Egyptian Statistical Journal, 2019
In this paper, a comparison of  Bayesian estimators using non-informative priors under different loss functions, assuming  that both the stress and the strength are independently indentically burr XII random variables.
M. Yahya
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   +4 more sources

Bayesian Estimation of the Parameter of the Exponential Distribution with Different Priors under Symmetric and Asymmetric Loss Functions [PDF]

Engineering and Technology Journal, 2014
The objective of this study is to compare the performance of some Bayesian estimators for the shape parameter of the exponential distribution. We considered three priors: the extension of Jeffreys as non- informative prior information, as well as the ...
Tasnim H.K. AlBaldawi
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   +2 more sources

Estimation of Entropy for Weibull Distribution Based on Record Values

Journal of Statistical Theory and Applications (JSTA), 2021
In this paper, estimation of entropy for Weibull distribution based on record values is considered. Maximum likelihood estimation and Bayes estimation for Shannon entropy and Renyi entropy have been considered based on record values. Bayes estimators are
Manoj Chacko, P. S. Asha
doaj   +1 more source

Approximate Bayes Estimation for Log-Dagum Distribution

Cumhuriyet Science Journal, 2019
In this article, the approximate Bayes estimationproblem for the log-Dagum distribution with three parameters is considered.Firstly, the maximum likelihood estimators and asymptotic confidence intervalsbased on these estimators for unknown parameters of ...
Caner Tanış, Merve Çokbarlı, Buğra Saraçoğlu   +2 more
doaj   +1 more source

Universal Bayes Estimators

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