Results 21 to 30 of about 25,682 (291)
On Some Classes of Estimators Derived from the Positive Part of James–Stein Estimator
Journal of Mathematics, 2023 This work consists of developing shrinkage estimation strategies for the multivariate normal mean when the covariance matrix is diagonal and known. The domination of the positive part of James–Stein estimator (PPJSE) over James–Stein estimator (JSE ...
Abdenour Hamdaoui +5 more
doaj +1 more source
Improved estimators for the rate parameter of gamma model using asymptotic properties
Heliyon, 2021 In this paper we proposed three estimators namely linear shrinkage, preliminary test and shrinkage preliminary test for the rate parameter of univariate gamma.
Nana Kena Frempong +3 more
doaj +1 more source
Sequential Shrinkage Estimation
The Annals of Statistics, 1987 Let \(X_ 1,X_ 2,\ldots\) \((p\times 1)\) be i.i.d. \(N(\theta,\sigma^2V)\), with \(\theta\), \(\sigma\) unknown and \(V\) a known \(p\times p\) positive definite matrix. If it is decided to stop at stage \(n\) and \(\theta\) is estimated by \(\delta_ n=\delta_ n(X_ 1,\ldots,X_ n)\), then the loss will be \(L(\theta,\delta_ n)'Q(\delta_ n-\theta)+cn ...
Ghosh, Malay +2 more
openaire +3 more sources
Double-Stage Shrinkage Estimation of Reliability Function for Burr XII Distribution
Iraqi Journal for Computer Science and Mathematics, 2022 This study is concerned with the problem of estimating the reliability function of the parameters of the two-parameter Burr XII distribution when the data are complete.
Iman Jalil Atewi +2 more
doaj +1 more source
IEEE Access, 2019 Shrinkage regularization is an effective strategy to estimate the covariance matrix of multi-variate random vector in small sample scenarios. The purpose of this paper is to propose improved linear shrinkage estimators of covariance matrix as two types ...
Bin Zhang, Jie Zhou, Jianbo Li
doaj +1 more source
Small Area Shrinkage Estimation
Statistical Science, 2012 The need for small area estimates is increasingly felt in both the public and private sectors in order to formulate their strategic plans. It is now widely recognized that direct small area survey estimates are highly unreliable owing to large standard errors and coefficients of variation.
Datta, G., Ghosh, M.
openaire +4 more sources
Bayesian Fusion Estimation via t Shrinkage [PDF]
Sankhya A, 2019 Shrinkage prior has gained great successes in many data analysis, however, its applications mostly focus on the Bayesian modeling of sparse parameters. In this work, we will apply Bayesian shrinkage to model high dimensional parameter that possesses an unknown blocking structure.
Qifan Song, Guang Cheng
openaire +3 more sources
Open Mathematics, 2022 One of the most common challenges in multivariate statistical analysis is estimating the mean parameters. A well-known approach of estimating the mean parameters is the maximum likelihood estimator (MLE).
Benkhaled Abdelkader +4 more
doaj +1 more source
Estimating the Variance of an Exponential Distribution in the Presence of Large True Observations
Austrian Journal of Statistics, 2016 The present paper discusses some classes of shrinkage estimators for the variance of the exponential distribution in the presence of large true observations when some a priori or guessed interval containing the variance parameter is available from some ...
Housila P. Singh, Vankim Chander
doaj +1 more source
Nonparametric Stein-type Shrinkage Covariance Matrix Estimators in High-Dimensional Settings [PDF]
, 2014 Estimating a covariance matrix is an important task in applications where the number of variables is larger than the number of observations. Shrinkage approaches for estimating a high-dimensional covariance matrix are often employed to circumvent the ...
Touloumis, Anestis
core +2 more sources