Title :
An interval nonparametric regression method
Author :
de A Fagundes, Roberta A. ; Filho, Ricardo J. A. Queiroz ; de Souza, Renata M. C. R. ; Cysneiros, Francisco Jose A.
Author_Institution :
Centro de Inf., Univ. Fed. de Pernambuco, Recife, Brazil
Abstract :
This paper proposes a nonparametric multiple regression method for interval data. Regression smoothing investigates the association between an explanatory variable and a response variable. Here, each interval variable of the input data is represented by its range and center and a smooth function between a pair of vector of interval variables is defined. In order to test the suitability of the proposed model, a simulation study is undertaken and an application using thirteen project data of the NASA repository to estimate interval software size is also considered. These real data represent variability and/or uncertainty innate to the project data. The prediction quality is assessed by a mean magnitude of relative errors calculated from test data.
Keywords :
data analysis; regression analysis; interval data; interval nonparametric regression method; interval software size; nonparametric multiple regression method; regression smoothing; smooth function; Data models; Kernel; NASA; Noise; Standards; Vectors;
Conference_Titel :
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4673-6128-6
DOI :
10.1109/IJCNN.2013.6706983