Treffer: Modified Ridge Parameters for Seemingly Unrelated Regression Model

Title:
Modified Ridge Parameters for Seemingly Unrelated Regression Model
Authors:
ZEEBARI, Z, SHUKUR, G, KIBRIA, B. M. G
Source:
Communications in statistics. Theory and methods. 41(7-9):1675-1691
Publisher Information:
Philadelphia, PA: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Généralités, General topics, Lois de probabilités, Distribution theory, Inférence linéaire, régression, Linear inference, regression, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Analyse numérique, Numerical analysis, Análisis numérico, Distribution statistique, Statistical distribution, Distribución estadística, Erreur moyenne, Mean error, Error medio, Estimation biaisée, Biased estimation, Estimación sesgada, Estimation sans biais, Unbiased estimation, Estimación insesgada, Grand échantillon, Large sample, Modèle régression, Regression model, Modelo regresión, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode statistique, Statistical method, Método estadístico, Méthode stochastique, Stochastic method, Método estocástico, Régression pseudo orthogonale, Ridge regression, Regresión ridge, Régression statistique, Statistical regression, Regresión estadística, Simulation statistique, Statistical simulation, Simulación estadística, Théorie approximation, Approximation theory, 62E17, 62J07, 62Jxx, 65C05, Estimateur rétrécissement, Régression multivariable, Multivariate regression, Modified SUR ridge regression, Monte Carlo simulations, Multicollinearity, TMSE
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Economics, Finance, and Statistics, Jonkoping University, Jönköping, Sweden
Departments of Economics and Statistics, Center for Labor Market and Discrimination Studies, Linnaeus University, Sweden
Department of Mathematics and Statistics, Florida International University, Miami, FL, United States
ISSN:
0361-0926
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=25906572
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.25906572
Database:
PASCAL Archive

Weitere Informationen

In this article, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine estimators of the ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified estimators of the ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge RMSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high, the unbiased SUR, estimator produces a smaller TMSEs.