Title :
Resistant Regression for Interval-Valued Data
Author :
Renan, Jobson ; Silva, Jornandes Dias ; Galdino, Sergio
Author_Institution :
Polytech. Sch., Pernambuco Univ., Recife, Brazil
Abstract :
This paper introduces two new approaches to fit univariate resistant linear regression models on interval-valued data. Linear regressions on interval-valued data gives point predictions. The prediction of the lower and upper bounds from interval-valued data of dependent variable are estimated from the fitted range resistant linear regression model. The new proposed methods should be used in presence of outliers.
Keywords :
data analysis; regression analysis; interval-valued data; range resistant linear regression model; resistant regression; univariate resistant linear regression model; Data analysis; Data models; Linear regression; Mathematical model; Predictive models; Random variables; Resistance; interval-valued data; resistant regression; symbolic data analysis;
Conference_Titel :
Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on
Conference_Location :
Ipojuca
DOI :
10.1109/BRICS-CCI-CBIC.2013.52