On the Possibilistic Approach to Linear Regression with Rounded or Interval-Censored Data
By: Michal Černý and Miroslav Rada
Open Access
|Jun 2011References
- Guo, P., Tanaka, H. (2006). Dual models for possibilistic regression analysis.51 (1), 253-266.
- Jun-peng, G.,Wen-hua, L. (2008). Regression analysis of interval data based on error theory. In:, Sanya, China, 2008, 552-555.
- Lee, H., Tanaka, H. (1998). Fuzzy regression analysis by quadratic programming reflecting central tendency.25 (1), 65-80.
- Lima Neto, E. de A., de Carvalho, F. de A. T. (2010). Constrained linear regression models for symbolic interval-valued variables.54 (2), 333-347.
- Moral-Arce, I., Rodríguez-Póo, J. M., Sperlich, S. (2011). Low dimensional semiparametric estimation in a censored regression model.102 (1), 118-129.
- Pan, W., Chappell, R. (1998). Computation of the NPMLE of distribution functions for interval censored and truncated data with applications to the Cox model.28 (1), 33-50.
- Zhang, X., Sun, J. (2010). Regression analysis of clustered interval-censored failure time data with informative cluster size.54 (7), 1817-1823.
- Inuiguchi, M., Fujita, H., Tanino, T. (2002). Robust interval regression analysis based on Minkowski difference. In:, vol. 4, Osaka, Japan, 2002, 2346-2351.
- Nasrabadi, E., Hashemi, S. (2008). Robust fuzzy regression analysis using neural networks.16 (4), 579-598.
- Hesmaty, B., Kandel, A. (1985). Fuzzy linear regression and its applications to forecasting in uncertain environment.15, 159-191.
- Hladík, M., černý, M. (2010). Interval regression by tolerance analysis approach.. Submitted, Preprint: KAM-DIMATIA Series 963.
- Hladík, M., černý, M. (2010). New approach to interval linear regression. In: Kasimbeyli, R., et al. (eds.),, Lithuania, 2010, 167-171.
- Tanaka, H., Lee, H. (1997). Fuzzy linear regression combining central tendency and possibilistic properties. In:, vol. 1, Barcelona, Spain, 1997, 63-68.
- Tanaka, H., Lee, H., (1998). Interval regression analysis by quadratic programming approach.6 (4), 473-481.
- Tanaka, H., Watada, J. (1988). Possibilistic linear systems and their application to the linear regression model.27 (3), 275-289.
- Černý, M., Rada, M. (2010). A note on linear regression with interval data and linear programming. In:, Slovakia: Kluwer, Iura Edition, 276-282.
- Dunyak, J. P., Wunsch, D. (2000). Fuzzy regression by fuzzy number neural networks.112 (3), 371-380.
- Huang, C.-H., Kao, H.-Y. (2009). Interval regression analysis with soft-margin reduced support vector machine.5579, Germany: Springer, 826-835.
- Ishibuchi, H., Tanaka, H., Okada, H. (1993). An architecture of neural networks with interval weights and its application to fuzzy regression analysis.57 (1), 27-39.
- Bentbib, A. H. (2002). Solving the full rank interval least squares problem.41 (2), 283-294.
- Gay, D. M. (1988). Interval least squares—a diagnostic tool. In: Moore, R. E., (ed.),, vol. 19, Boston, USA: Academic Press, 183-205.
- Sheppard, W. (1898). On the calculation of the most probable values of frequency constants for data arranged according to equidistant divisions of a scale.29, 353-380.
- Kendall, M. G. (1938). The conditions under which Sheppard's corrections are valid.101, 592-605.
- Eisenhart, C. (1947). The assumptions underlying the analysis of variance.3, 1-21.
- Schneeweiss, H., Komlos, J. (2008). Probabilistic rounding and Sheppard's correction.45, Department of Statistics, University of Munich. Available at:
- Di Nardo, E. (2010). A new approach to Sheppard's corrections., 19 (2), 151-162.
- Wimmer, G., Witkovský, V. (2002). Proper rounding of the measurement results under the assumption of uniform distribution.2 (1), 1-7.
- Wimmer, G., Witkovský, V., Duby, T. (2000). Proper rounding of the measurement results under normality assumptions.11, 1659-1665.
- Ziegler, G. (2004)., Germany: Springer.
- Avis, D., Fukuda, K. (1996). Reverse search for enumeration.65, 21-46.
- Ferrez, J.-A., Fukuda, K., Liebling, T. (2005). Solving the fixed rank convex quadratic maximization in binary variables by a parallel zonotope construction algorithm.166, 35-50.
- Grötschel, M., Lovász, L., Schrijver, A. (1993)., Germany: Springer.
DOI: https://doi.org/10.2478/v10048-011-0007-0 | Journal eISSN: 1335-8871
Language: English
Page range: 34 - 40
Published on: Jun 3, 2011
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Related subjects:
© 2011 Michal Černý, Miroslav Rada, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons License.