On the implementation of LIR: the case of simple linear regression with interval data-Reference-Cited by-同舟云学术

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On the implementation of LIR: the case of simple linear regression with interval data

Published:2013-11-05 Issue:3-4 Volume:29 Page:743-767
ISSN:0943-4062
Container-title:Computational Statistics
language:en
Short-container-title:Comput Stat

Author:

Cattaneo Marco E. G. V.,Wiencierz Andrea

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s00180-013-0459-9.pdf

Reference46 articles.

1. Alexandrov AD (2005) Convex polyhedra. Springer, Berlin

2. Beaton AE, Rubin DB, Barone JL (1976) The acceptability of regression solutions: another look at computational accuracy. J Am Stat Assoc 71:158–168

3. Bernholt T (2005) Computing the least median of squares estimator in time $$O(n^{d})$$ O ( n d ) . In: Gervasi O, Gavrilova ML, Kumar V, Laganà A, Lee HP, Mun Y, Taniar D, Tan CJK (eds) Computational science and its applications—ICCSA 2005. Springer, Berlin, pp 697–706

4. Buckley J, James I (1979) Linear regression with censored data. Biometrika 66:429–436

5. Carrizosa E, Plastria F (1995) The determination of a “least quantile of squares regression line” for all quantiles. Comput Stat Data Anal 20:467–479

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1. On the Generalization Performance of a Regression Model with Imprecise Elements;International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems;2017-09-04

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