On the weighted mixed Liu-type estimator under unbiased stochastic restrictions

2017 ◽  
Vol 46 (9) ◽  
pp. 7238-7248 ◽  
Author(s):  
Nilgun Yildiz
Keyword(s):  
Stochastic Restrictions

scholarly journals On the Preliminary Test Generalized Liu Estimator with Series of Stochastic Restrictions

2019 ◽  
Vol 18 (1) ◽  
pp. 113-131 ◽  
Author(s):  
Mohammad Hossein Karbalaee ◽  
Seyed Moahammad M. Tabatabaey ◽  
Mohammed Arashi ◽  
◽  
◽  
...  
Keyword(s):  
Preliminary Test ◽  
Liu Estimator ◽  
Stochastic Restrictions

A Cobb–Douglas type model with stochastic restrictions: formulation, local influence diagnostics and data analytics in economics

2019 ◽  
Vol 53 (4) ◽  
pp. 1693-1719 ◽  
Author(s):  
Francisco J. A. Cysneiros ◽  
Víctor Leiva ◽  
Shuangzhe Liu ◽  
Carolina Marchant ◽  
Paulo Scalco
Keyword(s):  
Data Analytics ◽  
Local Influence ◽  
Type Model ◽  
Influence Diagnostics ◽  
Stochastic Restrictions

A mean square error test when stochastic restrictions are used in regression

1974 ◽  
Vol 3 (8) ◽  
pp. 755-768 ◽  
Author(s):  
T.A. Yancey ◽  
G.G. Judge ◽  
M.E. Bock
Keyword(s):  
Mean Square Error ◽  
Mean Square ◽  
Stochastic Restrictions

scholarly journals New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model

2020 ◽  
Vol 17 (1(Suppl.)) ◽  
pp. 0361
Author(s):  
Mustafa Ismaeel Naif Alheety
Keyword(s):  
Regression Model ◽  
Simulation Study ◽  
Goodness Of Fit ◽  
Prior Information ◽  
Mean Squared Error ◽  
Numerical Example ◽  
Squared Error ◽  
Mixed Regression ◽  
The Mean ◽  
Stochastic Restrictions

This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

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