Results 21 to 30 of about 9,519 (266)
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
A Comparison Between the Bayesian and the Classical Estimators of Weibull Distribution
Journal of Kufa for Mathematics and Computer, 2013 In this paper ,we study estimation of two parameters of Weibull distribution .Methods of estimation used are maximum likelihood estimator (MLE) and Bayes. We compared the numerical results by simulation in MATLAB program.
Fadhil abdulabaas Alabadee +2 more
doaj +1 more source
SHRINKAGE ESTIMATOR FOR A SINGLE OBSERVATION IN N(Θ,V) PROBLEM WITH UNKNOWN VARIANCE [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2012 this search, Shrinkage Estimator has been studied for a Single Observation in N(θ,V) problem when variance is unknown. We proved that there is a relationship between Shrinkage Estimator and Normal Bayes Estimator.
AMER F. NASSAR
doaj +1 more source
Frontiers in Big Data, 2022 For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in Lehmann and Casella (1998) and Mao and Tang (2012).
Ying-Ying Zhang +5 more
doaj +1 more source
Data-Based Nonparametric Signal Filtration
Austrian Journal of Statistics, 2016 The problem of stochastic signal filtration under nonparametric uncertainties is considered. A probabilistic description of the signal process is assumed to be completely unknown. The Bayes estimator can not be constructed in this case.
Alexander V. Dobrovidov +1 more
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
Bayes and Non-Bayes Estimation Methods for the Parameter of Maxwell-Boltzmann Distribution
مجلة بغداد للعلوم, 2017 In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (
Baghdad Science Journal
doaj +1 more source
Estimation in the Koziol-Green Model Using a Gamma Process Prior
Austrian Journal of Statistics, 2016 The paper deals with nonparametric Bayes estimators in the Koziol-Green model of random censorship. A gamma process is assumed as a prior distribution for cumulative hazard rate and the Bayes estimator incorporating the proportional hazards censorship ...
Michal Friesl
doaj +1 more source
Intrinsic Bayesian estimation of linear time series models
Statistical Theory and Related Fields, 2021 Intrinsic loss functions (such as the Kullback–Leibler divergence, i.e. the entropy loss) have been used extensively in place of conventional loss functions for independent samples. But applications in serially correlated samples are scant.
Shawn Ni, Dongchu Sun
doaj +1 more source
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