Linearly admissible estimators of mean vector with respect to balanced loss function in multivariate statistics

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2013.854912 ◽

2015 ◽

Vol 45 (4) ◽

pp. 1063-1069 ◽

Author(s):

Ming-Xiang Cao ◽

Guang-Jun Shena

Keyword(s):

Multivariate Statistics ◽

Loss Function ◽

Balanced Loss Function ◽

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Bayes minimax estimation of the multivariate normal mean vector under balanced loss function

Statistics & Probability Letters ◽

10.1016/j.spl.2014.06.022 ◽

2014 ◽

Vol 93 ◽

pp. 96-101 ◽

Author(s):

S. Zinodiny ◽

S. Rezaei ◽

S. Nadarajah

Keyword(s):

Loss Function ◽

Minimax Estimation ◽

Multivariate Normal ◽

Balanced Loss Function ◽

Multivariate Normal Mean ◽

Normal Mean ◽

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Bayesian estimation of two value distribution parameter under a weighted balanced loss function

2011 International Conference on Multimedia Technology ◽

10.1109/icmt.2011.6002500 ◽

2011 ◽

Author(s):

Menglin Zhao ◽

Dong Songxiang

Keyword(s):

Bayesian Estimation ◽

Loss Function ◽

Value Distribution ◽

Distribution Parameter ◽

Balanced Loss Function

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Estimation of regression coefficients subject to exact linear restrictions when some observations are missing and quadratic error balanced loss function is used

Test ◽

10.1007/bf02595409 ◽

2005 ◽

Vol 14 (2) ◽

pp. 385-396 ◽

Author(s):

H. Toutenburg ◽

Shalabh

Keyword(s):

Loss Function ◽

Regression Coefficients ◽

Quadratic Error ◽

Balanced Loss Function ◽

Linear Restrictions

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Robust Bayesian inference in finite population sampling with auxiliary information under balanced loss function

Journal of the Korean Data and Information Science Society ◽

10.7465/jkdi.2014.25.3.685 ◽

2014 ◽

Vol 25 (3) ◽

pp. 685-696

Author(s):

Eunyoung Kim ◽

Dal Ho Kim

Keyword(s):

Bayesian Inference ◽

Loss Function ◽

Finite Population ◽

Auxiliary Information ◽

Finite Population Sampling ◽

Balanced Loss Function ◽

Population Sampling ◽

Robust Bayesian Inference

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Linearly admissible estimators on linear functions of regression coefficient under balanced loss function

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2018.1472788 ◽

2019 ◽

Vol 48 (11) ◽

pp. 2700-2706

Author(s):

MingXiang Cao ◽

DaoJiang He

Keyword(s):

Loss Function ◽

Regression Coefficient ◽

Linear Functions ◽

Balanced Loss Function

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Bayes Prediction for a Heteroscedastic Regression Superpopulation Model Using Balanced Loss Function

Communication in Statistics- Theory and Methods ◽

10.1080/03610920601125797 ◽

2007 ◽

Vol 36 (8) ◽

pp. 1565-1575 ◽

Author(s):

Ashok K. Bansal ◽

Priyanka Aggarwal

Keyword(s):

Loss Function ◽

Superpopulation Model ◽

Balanced Loss Function ◽

Bayes Prediction ◽

Heteroscedastic Regression

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On the admissibility of an estimator of a normal mean vector under a linex loss function

Annals of the Institute of Statistical Mathematics ◽

10.1007/bf02481143 ◽

1990 ◽

Vol 42 (4) ◽

pp. 657-669 ◽

Author(s):

Ahmad Parsian

Keyword(s):

Loss Function ◽

Linex Loss Function ◽

Normal Mean ◽

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Inadmissibility of the Stein-rule estimator under the balanced loss function

Journal of Econometrics ◽

10.1016/s0304-4076(98)00030-x ◽

1999 ◽

Vol 88 (1) ◽

pp. 193-201 ◽

Author(s):

Kazuhiro Ohtani

Keyword(s):

Loss Function ◽

Balanced Loss Function

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The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function

Econometric Reviews ◽

10.1080/07474939708800376 ◽

1997 ◽

Vol 16 (1) ◽

pp. 119-130 ◽

Author(s):

Kazuhiro Ohtani ◽

David E. A. Giles ◽

Judith A. Giles

Keyword(s):

Linear Regression ◽

Regression Model ◽

Loss Function ◽

Linear Regression Model ◽

Balanced Loss Function

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On Bayes Linear Unbiased Estimator Under the Balanced Loss Function

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2012.731128 ◽

2014 ◽

Vol 43 (24) ◽

pp. 5175-5194

Author(s):

Hongbing Qiu ◽

Ji Luo ◽

Shurong Zheng

Keyword(s):

Loss Function ◽

Unbiased Estimator ◽

Balanced Loss Function

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