| iRegression-package {iRegression} | R Documentation |
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 eufrasio@de.ufpb.br , Claudio A. V. de Souza Filho and Pedro R. D. Marinho
Maintainer: Eufrasio de A. Lima Neto eufrasio@de.ufpb.br
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.