On the loss of information due to fuzziness in experimental observations
- 49 Downloads
- 13 Citations
Abstract
The absence of exactness in the observation of the outcomes of a random experiment always entails a loss of information about the experimental distribution. This intuitive assertion will be formally proved in this paper by using a mathematical model involving the notions of fuzzy information and fuzzy information system (as intended by Tanaka, Okuda and Asai) and Zadeh's probabilistic definition. On the basis of this model we are first going to consider a family of measures of information enclosing some well-known measures, such as those defined by Kagan, Kullback-Leibler and Matusita, and then to establish methods for removing the loss of information due to fuzziness by increasing suitably the number of experimental observations.
Key words and phrases
Fuzzy information fuzzy information system non-parametric measures of directed divergence probability of a fuzzy event random experimentPreview
Unable to display preview. Download preview PDF.
References
- Casals, M. R., Gil, M. A. and Gil, P. (1986). The fuzzy decision problem: an approach to the problem of testing statistical hypotheses with fuzzy information, European J. Oper. Res., 27, 371–382.MathSciNetCrossRefGoogle Scholar
- Ferentinos, K. and Papaioannou, T. (1979). Loss of information due to groupings, Trans. 8th Prague Conf. on Inf. Theo., Stat. Dec. Func. and Ran. Proc., C, 87–94.Google Scholar
- Ferentinos, K. and Papaioannou, T. (1981). New parametric measures of information, Inform, and Control, 51, 193–208.MathSciNetCrossRefGoogle Scholar
- Ferentinos, K. and Papaioannou, T. (1982). Information in experiments and sufficiency, J. Statist. Plann. Inference, 6, 309–317.MathSciNetCrossRefGoogle Scholar
- Fisher, R. A. (1925). Theory of statistical estimation, Proc. Cambridge Philos. Soc., 22, 700–725.CrossRefGoogle Scholar
- Gil, M. A. (1988). Probabilistic-possibilistic approach to some statistical problems with fuzzy experimental observations, Combining Fuzzy Imprecision and Probabilistic Uncertainty in Decision-Making, (eds. J., Kacprzyk and M., Fedrizzi), pp. 286–306, Lecture Notes in Economics, No. 310, Springer-Verlag, Berlin.CrossRefGoogle Scholar
- Gil, M. A., López, M. T. and Gil, P. (1984). Comparison between fuzzy information systems, Kybernetes, 13, 245–251.MathSciNetCrossRefGoogle Scholar
- Gil, M. A., Corral, N. and Gil, P. (1985a). The fuzzy decision problem: an approach to the point estimation problem with fuzzy information, European J. Oper. Res., 22, 26–34.MathSciNetCrossRefGoogle Scholar
- Gil, M. A., López, M. T. and Gil, P. (1985b). Quantity of information; comparison between information systems: 1. Nonfuzzy states, 2. Fuzzy states, Fuzzy Sets and Systems, 15, 65–78, 129–145.MathSciNetCrossRefGoogle Scholar
- Kagan, A. M. (1963). On the theory of Fisher's amount of information, Soviet Math. Dokl., 4, 991–993.MATHGoogle Scholar
- Kale, K. (1964). A note on the loss of information due to grouping of observations, Biometrika, 51, 495–497.MathSciNetCrossRefGoogle Scholar
- Kullback, S. and Leibler, A. (1951). On information and sufficiency, Ann. Math. Statist., 22, 79–86.MathSciNetCrossRefGoogle Scholar
- Mathai, A. M. and Rathie, P. N. (1975). Basic Concepts in Information Theory and Statistics, Wiley, New Delhi.MATHGoogle Scholar
- Matusita, K. (1967). On the notion of affinity of several distributions and some of its applications. Ann. Inst. Statist. Math., 19, 181–192.MathSciNetCrossRefGoogle Scholar
- Okuda, T., Tanaka, H. and Asai, K. (1978). A formulation of fuzzy decision problems with fuzzy information, using probability measures of fuzzy events, Inform. and Control, 38, 135–147.MathSciNetCrossRefGoogle Scholar
- Rathie, P. N. (1973). Some characterization theorems for generalized measures of uncertainty and information, Metrika, 20, 122–130.MathSciNetCrossRefGoogle Scholar
- Rényi, A. (1961). On measures of entropy and information, Proc. Fourth Berkeley Symp. on Math. Statist. Prob., Vol. 1, 547–561, Univ. California Press, Berkeley.MATHGoogle Scholar
- Tanaka, H., Okuda, T. and Asai, K. (1979). Fuzzy information and decision in statistical model, Advances in Fuzzy Sets Theory and Applications, 303–320, North-Holland, Amsterdam.Google Scholar
- Zadeh, L. A. (1965). Fuzzy sets, Inform. and Control, 8, 338–353.CrossRefGoogle Scholar
- Zadeh, L. A. (1968). Probability measures of fuzzy events, J. Math. Anal. Appl., 23, 421–427.MathSciNetCrossRefGoogle Scholar
- Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1, 3–28.MathSciNetCrossRefGoogle Scholar