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15 articles for “Multicollinearity”
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Research ArticleOpen accessEvery word in the titleEstimation Methods for Multicollinearity Proplem Combined with High Leverage Data PointsMoawad El-Fallah, Abd El-SallamProblem statement: Least Squares (LS) method has been the most popular method for estimating the parameters of a model due to its optimal properties and ease of computation. LS estimated regression may be seriously affected by multicollinearity which is a near linear dependency between two or more explanatory variables in the regression models. Although LS estimates are unbiased in the … …Journal of Mathematics and Statistics, Vol. 7, Issue 2 · 18 May 2011 · 7,617 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEstimation under Multicollinearity: A Comparative Approach Using Monte Carlo MethodsD. A. Agunbiade, J. O. IyaniwuraProblem statement: A comparative investigation was done experimentally for 6 different Estimation Techniques of a just-identified simultaneous three-equation econometric model with three multi-collinear exogenous variables. Approach: The aim is to explore in depth the effects of the problems of multicollinearity and examine the sensitivity of findings to increasing sample sizes and increasing number of replications using the mean and total … …Journal of Mathematics and Statistics, Vol. 6, Issue 2 · 30 Jun 2010 · 7,531 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Estimations as a Remedy for Multicollinearity Caused by Multiple High Leverage PointsArezoo Bagheri, Habshah MidiProblem statement: The Least Squares (LS) method has been the most popular technique for estimating the parameters of a model due to its optimal properties and ease of computation. LS estimated regression may be seriously disturbed by multicollinearity which is a near linear dependency between two or more explanatory variables in the regression models. Even though LS estimates are unbiased … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 8,247 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEffect of Multicollinearity on Power Rates of the Ordinary Least Squares EstimatorsO.O. Alabi, Kayode Ayinde, T.O. OlatayoInferences on the parameter estimates of Ordinary Least Square (OLS) estimator in regression model when regressors exhibit multicollinearity is a problem in that large standard errors of the regression coefficients which cause low t-statistic value often result into the acceptance of the null hypothesis. This paper, therefore, makes efforts to investigate the effect of multicollinearity on the power rates of … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 7,880 accessesView PDFCite
Review ArticleOpen accessIn the keywordsThe use of Principal Component Regression and Time Series Analysis to Predict Nitrous Oxide Emissions in GhanaBenjamin Odoi, Lewis Brew, Christopher AttafuahThe disturbing pace of emanation of Nitrous Oxide (N2O) into the atmosphere and its calamitous impact on the environment, as monitored by many governmental agencies and researchers has become a wellspring of worry for many nations and therefore needs due attention. The study deployed nitrous oxide emissions from the three sectors to the total nitrous oxide emissions in Ghana over … …Energy Research Journal, Vol. 12, Issue 1 · 6 Jan 2021 · 8,597 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop SopipanThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive order p (AR (p)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Results showed that the multiple regressions based on PCA, … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 17 Apr 2013 · 6,958 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFORECASTING RETURNS FOR THE STOCK EXCHANGE OF THAILAND INDEX USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop Sopipan, Anchalee Sattayatham, Samruam ChongcharoenThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive Moving-Average order p and q (ARMA (p, q)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Afterwards, we forecast the volatility … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 18 Mar 2013 · 7,438 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Modification of the Ridge Type Regression EstimatorsMoawad El-Fallah Abd El-SalamProblem statement: Many regression estimators have been used to remedy multicollinearity problem. The ridge estimator has been the most popular one. However, the obtained estimate is biased. Approach: In this stuyd, we introduce an alternative shrinkage estimator, called modified unbiased ridge (MUR) estimator for coping with multicollinearity problem. This estimator is obtained from Unbiased Ridge Regression (URR) in the same … …American Journal of Applied Sciences, Vol. 8, Issue 1 · 31 Jan 2011 · 7,638 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTwo-Step Robust Diagnostic Method for Identification of Multiple High Leverage PointsArezoo Bagheri, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: High leverage points are extreme outliers in the X-direction. In regression analysis, the detection of these leverage points becomes important due to their arbitrary large effects on the estimations as well as multicollinearity problems. Mahalanobis Distance (MD) has been used as a diagnostic tool for identification of outliers in multivariate analysis where it finds the distance between normal … …Journal of Mathematics and Statistics, Vol. 5, Issue 2 · 30 Jun 2009 · 8,306 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Performance of Latent Root-M based RegressionHabshah Midi, Lau Ung HuaProblem statement: In the presence of multicollinearity, the estimation of parameters in multiple linear regression models by means of Ordinary Least Squares (OLS) is known to suffer severe distortion. An alternative approach was to use the modified OLS which was based on the latent roots and latent vectors of the correlation matrix of the independent and dependent variables. This procedure … …Journal of Mathematics and Statistics, Vol. 5, Issue 1 · 31 Mar 2009 · 8,654 accessesView PDFCite