Results 251 to 260 of about 263,469 (298)

Saddlepoint inference for rank-based k-sample tests in clustered survival trials. [PDF]

Sci Rep
Newer HA.
europepmc   +1 more source

ABR-UNet3D: Aspect-Aware Boundary-Resilient Attention for Robust Cardiac MRI Segmentation. [PDF]

Diagnostics (Basel)
Akyel S, Cetinkaya Z, Topaloglu F, Sert E.   +3 more
europepmc   +1 more source

The optimal extended balanced loss function estimators

Journal of Computational and Applied Mathematics, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Issam Dawoud
exaly   +4 more sources

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.
openaire   +2 more sources

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.
openaire   +2 more sources

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Estimation for the Multiple Regression Setup Using Balanced Loss Function

Communications in Statistics Part B: 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
exaly   +2 more sources

The Efficiency of Shrinkage Estimators with Respect to Zellner's Balanced Loss Function

Communications in Statistics - Theory and Methods, 2004
Abstract A setup with r uncorrelated linear models is considered. A generalization of Zellner's balanced loss function is proposed. Zellner's balanced loss function takes both error of estimation and goodness of fit into account. The classical loss function only considers error of estimation.
exaly   +2 more sources