@article{(Open Science Index):https://publications.waset.org/pdf/6479,
	  title     = {Computational Aspects of Regression Analysis of Interval Data},
	  author    = {Michal Cerny},
	  country	= {},
	  institution	= {},
	  abstract     = {We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.
},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {5},
	  number    = {9},
	  year      = {2011},
	  pages     = {1469 - 1476},
	  ee        = {https://publications.waset.org/pdf/6479},
	  url   	= {https://publications.waset.org/vol/57},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 57, 2011},
	}