iRegression-package: Regression Methods for Interval-Valued Variables

In iRegression: Regression Methods for Interval-Valued Variables

Description

Contains some important regression methods for interval-valued variables. For each method, it is available the fitted values, residuals and some goodness-of-fit measures.

Details

Package:	iRegression
Type:	Package
Version:	1.2.1
Date:	2016-07-16
License:	GPL (>= 2)
LazyLoad:	yes

Some available functions: cm, MinMax, crm, ccrm, bivar

Author(s)

Eufrasio de A. Lima Neto [e-mail] , Claudio A. V. de Souza Filho and Pedro R. D. Marinho

Maintainer: Eufrasio de A. Lima Neto [e-mail]

Acknowledgments: The authors would like to thank CNPq (Brazilian Agency) for their financial support.

References

Billard, L. and Diday, E. (2000) Regression analysis for interval-valued data. Data Analysis, Classification and Related Methods: Proceedings of the Seventh Conference of the International Federation of Classification Societies, Springer-Verlag, pp. 369-374.

Lima Neto, E.A. and De Carvalho, F.A.T. (2008). Centre and range method to fitting a linear regression model on symbolic interval data. Computational Statistics and Data Analysis, 52, 1500–1515.

Lima Neto, E.A. and De Carvalho, F.A.T. (2010). Constrained linear regression models for symbolic interval-valued variables. Computational Statistics and Data Analysis, 54, 333–347.

Lima Neto, E. A., Cordeiro, G. and De Carvalho, F.A.T. (2011). Bivariate symbolic regression models for interval-valued variables. Journal of Statistical Computation and Simulation (Print), 81, 1727–1744.

iRegression documentation built on May 2, 2019, 8:24 a.m.