Results 251 to 260 of about 1,737,261 (319)

Bayesian Estimation of Regression Coefficients Under Extended Balanced Loss Function

Communications in Statistics - Theory and Methods, 2014
Appreciating the desirability of simultaneously using both the criteria of goodness of fitted model and clustering of estimates around true parameter values, an extended version of the balanced loss function is presented and the Bayesian estimation of regression coefficients is discussed.
Anoop Chaturvedi, null Shalabh
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Estimation for the Multiple Regression Setup Using Balanced Loss Function

Communications in Statistics - Simulation and Computation, 2012
Consider the estimation problem for the multiple linear regression (MLR) setup, under the balanced loss function (BLF), where goodness of fit and precision of estimation are modeled using either squared error loss (SEL) or linear exponential (LINEX) loss functions.
Raghu Nandan Sengupta, Sachin Srivastava
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On Bayes Linear Unbiased Estimator Under the Balanced Loss Function

Communications in Statistics - Theory and Methods, 2014
In this paper, the Bayes linear unbiased estimator (Bayes LUE) is derived under the balanced loss function. Moreover, the superiority of Bayes LUE over ordinary least square estimator is studied under the mean square error matrix criterion and Pitman closeness criterion.
Hongbing Qiu, Ji Luo, Shurong Zheng
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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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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 note on Pitman's measure of closeness with balanced loss function

Statistics, 2012
In this note, we consider the problem of estimating an unknown parameter θ in the sense of the Pitman's measure of closeness (PMC) using the balanced loss function (BLF). We show that the PMC comparison of estimators under the BLF can be reduced to the PMC comparison under the usual absolute error loss. The Pitman-closest estimators of the location and
M. J. Jozani
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Custom Weighted Balanced Loss function for Covid 19 Detection from an Imbalanced CXR Dataset

International Conference on Pattern Recognition, 2022
In this paper, we have proposed a novel framework, that is ResNet-18 model along with Custom Weighted Balanced loss function, in order to automatically detect Covid-19 disease from a highly imbalanced Chest X-Ray (CXR) dataset.
Mrinal Tyagi, Santanu Roy, Vibhuti Bansal   +2 more
semanticscholar   +1 more source

A Novel Loss Function for Optical and SAR Image Matching: Balanced Positive and Negative Samples

IEEE Geoscience and Remote Sensing Letters, 2022
Image matching is a primary technology for optical and synthetic aperture radar (SAR) image fusion but often shows limited performance due to the highly nonlinear differences between optical and SAR modalities.
Yueping He, Xueqian Wang, Yiming Zhang, Yu Liu, Zhizhuo Jiang, Gang Li, You He   +6 more
semanticscholar   +1 more source

An Appreciation of Balanced Loss Functions Via Regret Loss

Communications in Statistics - Theory and Methods, 2014
We examine balanced loss functions, which account for both estimation error and goodness of fit (or proximity to a “target” estimator), in terms of their regret losses, providing new insight and interpretations. This also shows a connection between quadratic balanced loss and usual quadratic loss, which easily converts frequentist and Bayesian results ...
Tapan K. Nayak, Bimal Sinha
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Generalized Liu Type Estimators Under Zellner's Balanced Loss Function

Communications in Statistics - Theory and Methods, 2005
ABSTRACT In regression analysis, ridge regression estimators and Liu type estimators are often used to overcome the problem of multicollinearity. These estimators have been evaluated using the risk under quadratic loss criterion, which places sole emphasis on estimators′ precision. The traditional mean square error (MSE) as the measure of efficiency of
Akdeniz F., Wan A.T.K., Akdeniz E.
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