论文信息 - A note on the operativeness of Neyman-Pearson tests with fuzzy information

A note on the operativeness of Neyman-Pearson tests with fuzzy information

Abstract In a previous paper we have studied the extension of the Neyman-Pearson optimality criterion of testing statistical hypotheses when the available experimental information involves fuzzy imprecision. This extension usually becomes unmanageable for small samples. Nevertheless. we will verify that when the sample size is large enough the application of the Central Limit Theorem determines an operative extension.

María Rosa Casals | María Ángeles Gil

[1] M. A. Gil,et al. Fuzziness and loss of information in statistical problems , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[2] L. Zadeh. Probability measures of Fuzzy events , 1968 .

[3] H. Tanaka,et al. A Formulation of Fuzzy Decision Problems with Fuzzy Information using Probability Measures of Fuzzy Events , 1978, Inf. Control..

[4] Pedro Gil,et al. The fuzzy decision problem: An approach to the problem of testing statistical hypotheses with fuzzy information , 1986 .

[5] Pedro Gil,et al. On the use of Zadeh's probabilistic definition for testing statistical hypotheses from fuzzy information , 1986 .

[6] B. Natvig. Possibility versus probability , 1983 .

[7] María Ángeles Gil,et al. Probabilistic-Possibilistic Approach to Some Statistical Problems with Fuzzy Experimental Observations , 1988 .

[8] Pedro Gil,et al. The minimum inaccuracy estimates in χ2 tests for goodness of fit with fuzzy observations , 1988 .