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23 results for “Ordinary Least Square”
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Research ArticleOpen accessIn the abstractRural and Urban Attitudes toward Immigrants in the U.S. Midwest and Great PlainsMiguel Ceballos, Oksana Yakushko, Courtney LyonsRecent immigration has transformed much of the Midwest and Great Plains regions of the United States, affecting its rural and urban areas through dramatic increases in the foreign-born population and in particular Latino immigrant populations. This study examines three theories of prejudice: Perceptions of threat, contact with immigrants and a cosmopolitanism outlook, in predicting rural and urban attitudes toward immigrants … …Journal of Social Sciences, Vol. 10, Issue 4 · 7 Jan 2015 · 8,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractGAUSSIAN COPULA MARGINAL REGRESSION FOR MODELING EXTREME DATA WITH APPLICATIONSutikno, Heri Kuswanto, Iis Dewi RatihRegression is commonly used to determine the relationship between the response variable and the predictor variable, where the parameters are estimated by Ordinary Least Square (OLS). This method can be used with an assumption that residuals are normally distributed (0, σ2). However, the assumption of normality of the data is often violated due to extreme observations, which are often found … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 4 Apr 2014 · 7,620 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDYAnwar Fitrianto, Lee Ceng YikWhen independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS) method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 3 Jan 2014 · 8,540 accessesView PDFCite
Research ArticleOpen accessIn the abstractEVIDENCE OF THE ENVIRONMENTAL KUZNETS CURVE: IMPLICATIONS OF INDUSTRIAL TRADE DATAJamalludin Sulaiman, Azlinda Azman, Behnaz SabooriThis study examines the dynamic relationship between CO2 emissions and economic growth in Malaysia for the period of 1980-2004. The evidence of the Environmental Kuznets Curve (EKC) is tested by including energy consumption, dirty export from Malaysia to China and dirty import from China to Malaysia based on the two and three-digit ISIC data which reflect pollution-intensive manufacturing. Using dirty … …American Journal of Environmental Sciences, Vol. 9, Issue 2 · 26 Mar 2013 · 7,251 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpatial Durbin Model to Identify Influential Factors of DiarrheaRokhana Dwi Bekti, SutiknoProblem statement: An analysis of regression modeling which influenced by the characteristics of the region is very important. That modeling is the spatial autoregressive model. One type of spatial autoregressive model is a Spatial Durbin Model (SDM), which performs a lag effect of the dependent and independent variables. This model was developed because the dependencies in the spatial relationships doesn’t … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 8,282 accessesView PDFCite
Research ArticleOpen accessIn the abstractTime-Delay Estimation using the Characteristic Roots of Delay Differential EquationsSun Yi, Wonchang Choi, Taher Abu-LebdehProblem statement: For ordinary dynamic systems (i.e., non-delayed), various methods such as linear least-squares, gradient-weighted least-squares, Kalman filtering and other robust techniques have been widely used in signal processing, robotics, civil engineering. On the other hand, time-delay estimation of systems with unknown time-delay is still a challenging problem due to difficulty in formulation caused. Approach: The presented method makes use … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 7 Apr 2012 · 8,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractLinear Regression Model Selection Based on Robust Bootstrapping TechniqueHassan S. Uraibi, Habshah Midi, Bashar A. Talib, Jabar H. YousifProblem statement: Bootstrap approach had introduced new advancement in modeling and model evaluation. It was a computer intensive method that can replace theoretical formulation with extensive use of computer. The Ordinary Least Squares (OLS) method often used to estimate the parameters of the regression models in the bootstrap procedure. Unfortunately, many statistics practitioners are not aware of the fact that … …American Journal of Applied Sciences, Vol. 6, Issue 6 · 30 Jun 2009 · 7,876 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeterminants of Intra-Industry Trade between Zimbabwe and its Trading Partners in the Southern African Development Community Region (1990-2006)Tafirenyika Sunde, C. Chidoko, J. ZivanomoyoProblem statement: The main objective of this study was to establish the determinants of intra industry trade between Zimbabwe and its trading partners in the Southern African Development Community (SADC) region. The study was mainly motivated by the need to establish the type of goods that Zimbabwe trades with its trading partners. Approach: The study also wanted to prove the … …Journal of Social Sciences, Vol. 5, Issue 1 · 31 Mar 2009 · 8,054 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe 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
Research ArticleOpen accessIn the abstractA Comparative Study of the Performances of the OLS and some GLS Estimators when Stochastic Regressors are both Collinear and Correlated with Error TermsKayode AyindeThe Classical Linear Regression Model assumes that regressors are non – stochastic, independent and uncorrelated with the error terms. These assumptions are not always tenable especially where regressors are not often assumed fixed in repeated sampling. In this paper, with stochastic regressors, the performances of the Ordinary Least Square (OLS) and some Generalized Least Square (GLS) estimators are investigated and … …Journal of Mathematics and Statistics, Vol. 3, Issue 4 · 31 Dec 2007 · 7,343 accessesView PDFCite