Results 141 to 150 of about 1,057,367 (187)

Sensorimotor function and standing balance in older adults with transtibial limb loss

Clinical Biomechanics, 2023
Limited research has focused on older prosthesis users despite the expected compounded effects of age and amputation on sensorimotor function, balance, and falls. This study compared sensorimotor factors and standing balance between older individuals with and without transtibial amputation, hypothesizing that prosthesis users would demonstrate worse ...
Matthew J, Major, Rebecca L, Stine
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Gradient Analysis of Loss Function Based on System Balance

2020
In recent years, deep learning has been widely used in various fields of social life. The theoretical understanding on how it works also makes people curious.
Suman Xia, Cheng Cheng, Haoyuan Wang, Xuguang Wang   +3 more
openaire   +1 more source

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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Estimation of a normal mean relative to balanced loss functions

Statistical Papers, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sanjari Farsipour, N., Asgharzadeh, A.
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Constrained Bayes and Empirical Bayes Estimation with Balanced Loss Functions

Communications in Statistics - Theory and Methods, 2007
This article develops constrained Bayes and empirical Bayes estimators under balanced loss functions. In the normal-normal example, estimators of the mean squared errors of the EB and constrained EB estimators are provided which are correct asymptotically up to O(m −1), m denoting the number of strata.
Malay Ghosh, Myung Joon Kim, Dalho Kim
openaire   +1 more source

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 on linear functions of regression coefficient under balanced loss function

Communications in Statistics - Theory and Methods, 2019
Linearly admissible estimators on linear functions of regression coefficient are studied in a singular linear model and balanced loss when the design matrix has not full column rank.
MingXiang Cao, DaoJiang He
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Balanced Ridge Estimator of Coefficient in Linear Model under a Balanced Loss Function (I)

2011
Based on the conception of Zellner’s Balanced Loss, considering the goodness of fitting and the accuracy of Ridge Estimator. the paper constructed the balanced loss function and put forward Balanced Ridge estimation of coefficient in linear model, also obtained the property of Balanced Ridge Estimator superior to Least Squares Estimator and ...
Wenke xu, Fengri Li
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Simultaneous estimation of the multivariate normal mean under balanced loss function

Communications in Statistics - Theory and Methods, 1997
This paper considers simultaneous estimation of multivariate normal mean vector using Zellner's(1994) balanced loss function which is defined as follows: where 0 < w < 1 and for i = 1,…,p and j = 1,…,n, Xij is distributed as normal with mean θi and variance 1. It is shown that the sample mean, X, is admissible when p
Younshik Chung, Chansoo Kim
openaire   +1 more source