Results 151 to 160 of about 1,057,367 (187)

Linearly admissible estimators of stochastic regression coefficient under balanced loss function

Statistics, 2013
The admissibility of linear estimators in a linear model with stochastic regression coefficient is investigated under a balanced loss function. The sufficient and necessary conditions for linear estimators to be admissible in classes of homogeneous and non-homogeneous linear estimators are obtained, respectively.
Mingxiang Cao, Xingzhong Xu, Daojiang He
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A perceptually balanced loss function for short-time spectral amplitude estimation

2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684), 2003
Summary form only given. We present a novel approach to audio signal enhancement based on psychoacoustic principles. Specifically, we describe a short-time spectral amplitude estimator whose form comprises a weighted sum of the minimum mean-square error solution and the observed spectral value, where the weighting factor is given by the ratio of the ...
P.J. Wolfe, S.J. Godsill
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Effect of hearing aids on static balance function in elderly with hearing loss

Gait & Posture, 2017
While a few studies have investigated the relationship between hearing acuity and postural control, little is known about the effect of hearing aids on postural stability in elderly with hearing loss. The aim was to compare static balance function between elderly with hearing loss who used hearing aids and those who did not use.
Hossein, Negahban, Mahtab, Bavarsad Cheshmeh Ali, Gholamhossein, Nassadj   +2 more
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Bayesian and Non-Bayesian Estimation Using Balanced Loss Functions

1994
Balanced Loss Functions (BLFs) which reflect both goodness of fit and precision of estimation are described. Optimal estimates relative to BLFs are derived for estimation of a scalar mean, a vector mean and a vector of regression coefficients. Properties of these estimates are compared with those of maximum likelihood (ML) estimates and Bayesian ...
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Shrinkage estimation for spherically symmetric distributions under modified balanced loss functions

Summary: We focus on the problem of estimating the average vector \(\theta=(\theta_1,\dots,\theta_d)\) of a random vector \(X\in\mathbb{R}^d\) which follows a spherically symmetric distribution. We consider modified balanced loss functions of the form: \par (i) \(L_{\omega,\delta_0,\rho}(\delta,\theta)=\omega\rho(\|\delta-\delta_0\|^2)+(1-\omega)\rho(\|
Hobbad, Lahoucine, Alahiane, Mohamed, Ouassou, Idir, Rachdi, Mustapha   +3 more
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Bayesian and Robust Bayesian analysis under a general class of balanced loss functions

Statistical Papers, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jafari Jozani, Mohammad, Marchand, Éric, Parsian, Ahmad   +2 more
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Linearly admissible estimators of the common mean parameter under balanced loss function

Communications in Statistics - Theory and Methods, 2017
ABSTRACTAdmissibility of linear estimators of the common mean parameter is investigated in the context of a linear model under balanced loss function. Sufficient and necessary conditions for linear estimators to be admissible in classes of homogeneous and non homogeneous linear estimators are obtained, respectively.
Mingxiang Cao, Xingzhong Xu
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Least squares estimators in measurement error models under the balanced loss function

Test, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bayes Prediction for a Stratified Regression Superpopulation Model Using Balanced Loss Function

Communications in Statistics - Theory and Methods, 2010
We consider the stratified regression superpopulation model and obtain Bayes predictor of the finite population mean under Zellner's two-criterion balanced loss function (BLF). BLF predictor simplifies to a linear combination of the sample and predictive means. Furthermore, it reduces to some of the well-known classical and Bayes predictors.
Ashok K. Bansal, Priyanka Aggarwal
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Inadmissibility of the Stein-rule estimator under the balanced loss function

Journal of Econometrics, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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