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26 results for “Robust Regression”
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Research ArticleOpen accessEvery word in the titleA Robust Rescaled Moment Test for Normality in RegressionMd. Sohel Rana, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: Most of the statistical procedures heavily depend on normality assumption of observations. In regression, we assumed that the random disturbances were normally distributed. Since the disturbances were unobserved, normality tests were done on regression residuals. But it is now evident that normality tests on residuals suffer from superimposed normality and often possess very poor power. Approach: This study … …Journal of Mathematics and Statistics, Vol. 5, Issue 1 · 31 Mar 2009 · 8,260 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Logistic Regression to Static Geometric Representation of RatiosAlireza Bahiraie, Noor Akma Ibrahim, A.K.M. Azhar, Ismail Bin MohdProblem statement: Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-salacity were solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. This new method would be a general methodological guideline associated with financial data and bankruptcy risk. Approach: We proposed the use of a new measure of risk, … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 8,216 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLinear 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 accessEvery word in the titleRobust Outlier Detection in Linear RegressionNethal K. Jajo, Xizhi WuNew methodology of robust outlier detection based on Robustly Studentized Robust Residuals (RSRR) examination is well established in linear regression analysis. Two new robust location estimators of linear regression parameters are developed in simple and multiple cases. Based on these robust estimators we obtain RSRR. We used RSRR to derive a new measure of distance to be used in outlier … …American Journal of Applied Sciences, Vol. 1, Issue 2 · 30 Jun 2004 · 6,933 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEstimation 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 accessIn the keywordsDrinking Wine at Home: Hedonic Analysis of Sicilian Wines Using Quantile RegressionGiuseppe Di Vita, Francesco Caracciolo, Luigi Cembalo et al.In recent decades, the Sicilian wine industry has experienced a booming expansion because of the growing preferences of Italian consumers for Sicilian wines, especially in extra-regional markets. These consumers have been paying closer attention to Sicilian premium wines. For this reason, the objective of this study is to inform professional investors and wine managers about the consumer preferences with respect … …American Journal of Applied Sciences, Vol. 12, Issue 10 · 14 Oct 2015 · 7,210 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIncome Distribution and Health Status: Econometric Evidence from OECD CountriesVasudeva N.R. MurthyThis research note, using a cross-sectional sample consisting of 27 Organization for Economic Co-operation and Development countries (OECD) for the reference year 2002, empirically examines the relationship between health status as measured by infant mortality and the degree of income inequality, given the effect of certain controlled variables. The empirical findings based on the estimation by robust econometric methods, show … …American Journal of Applied Sciences, Vol. 4, Issue 4 · 30 Apr 2007 · 7,251 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting CO2 Emissions Using Multivariate Regression: Assessing the Impact of Pandemics and Industrial RevolutionsYoussef Mekki, Chouaib Moujahdi, Noureddine Assad, Aziz DahbiThis paper explores the prediction of CO2 emissions usingMultivariate Regression models, incorporating the influence of significanthistorical events such as pandemics and industrial revolutions. Whileexisting research primarily focuses on carbon emissions alone in forecastingmodels, this study emphasizes the importance of incorporating multiplefactors for a comprehensive understanding of CO2 dynamics. Beyondemissions, factors such as socioeconomic indicators, industrial activities,environmental policies, and historical events … …Journal of Computer Science, Vol. 21, Issue 7 · 23 Jul 2025 · 3,426 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Collinearity Indices for Linear Models in Agricultural TrialsDanny Villegas Rivas, José M. Palacios Sánchez, Cristina A. Alzamora Rivero et al.The deleterious consequences of collinearity in linear regression on the precision of estimators of regression coefficients and the interpretability of the fitted model are widely recognized. In this study, we compare several methodologies for assessing collinearity in linear models and explore the effect of outliers on collinearity. The robustness of collinearity measures (individual and overall) is validated through two detailed … …OnLine Journal of Biological Sciences, Vol. 24, Issue 2 · 28 Dec 2023 · 6,491 accessesView PDFCite