A Simple but Efficient Approach for Testing Fuzzy Hypotheses

Abbas Parchami1, S. Mahmoud Taheri2, Bahram Sadeghpour Gildeh3, Mashaallah Mashinchi1
1Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
2Faculty of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran
3Department of Statistics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran

Tóm tắt

In this paper, a new method is proposed for testing fuzzy hypotheses based on the following two generalized p-values: (1) the generalized p-value of null fuzzy hypothesis against alternative fuzzy hypothesis and (2) the generalized p-value of alternative fuzzy hypothesis against null fuzzy hypothesis. In the proposed method, each generalized p-value is formulated on the basis of Zadeh’s probability measure of fuzzy events. The introduced p-value method has several advantages over the common p-value methods for testing fuzzy hypotheses. A few illustrative examples and also an agricultural example, based on a real-world data set, are given to clarify the proposed method.

Tài liệu tham khảo

Arefi, M, Taheri, SM: Testing fuzzy hypotheses using fuzzy data based on fuzzy test statistic. J. Uncertain Sys. 5, 45–61 (2011). Arefi, M, Taheri, SM: A new approach for testing fuzzy hypotheses based on fuzzy data. Int. J. Comput. Syst. 6, 318–327 (2013). Arnold, BF: An approach to fuzzy hypothesis testing. Metrika. 44, 119–126 (1996). Chachi, J, Taheri, SM, Viertl, R: Testing statistical hypotheses based on fuzzy confidence intervals. Austrian. J. Stat. 41, 267–286 (2012). Emadi, M, Arghami, N: Some measures of support for statistical hypotheses. J. Stat. Theory and Appl. 2, 165–176 (2003). Denœ ux, T, Masson, MH, Hébert, PA: Nonparametric rank-based statistics and significance tests for fuzzy data. Fuzzy Sets and Syst. 153, 1–28 (2005). Fazlalipor Miyandoab, M, Arzideh, K, Farbod, D: Fuzzy hypothesis testing with fuzzy data by using fuzzy p-value. Acta Univ. Apulensis. 32, 293–307 (2012). Filzmoser, P, Viertl, R: Testing hypotheses with fuzzy data: the fuzzy p-value. Metrika. 59, 21–29 (2004). Geyer, C, Meeden, G: Fuzzy confidence intervals and P-values. Stat. Sci. 20, 358–387 (2005). Ivani, R: The effect of various sources and amounts of organic fertilizer on bioavailability Zn and Cd in soil, M.Sc. Thesis, Faculty of Water and Soil. University of Tehran, Iran (2007). Knight, K: Mathematical Statistics. Chapman & Hall/CRC, Boca Raton (2000). Pais, I, Benton, JJ: The Handbook of Trace Elements. St. Lucie Press, Florida (1997). Parchami, A, Ivani, R, Mashinchi, M: An application of testing fuzzy hypotheses: a soil study on bioavailability of Cd. Scientia Iranica. 18, 470–478 (2011). Parchami, A, Taheri, SM, Mashinchi, M: Fuzzy p-value in testing fuzzy hypotheses with crisp data. Stat. Papers. 51, 209–226 (2010). Parchami, A, Taheri, SM, Mashinchi, M: Testing fuzzy hypotheses based on vague observations: a p-value approach. Stat. Papers. 53, 469–484 (2012). Royall, R: Statistical Evidence: A Likelihood Paradigm. Chapman and Hall/CRC, Florida (1997). Royall, R: On probability of observing misleading statistical evidence. J. Am. Stat. Assoc. 95, 760–768 (2000). Taheri, SM, Behboodian, J: Neyman-Pearson Lemma for fuzzy hypotheses testing. Metrika. 49, 3–17 (1999). Tanaka, H, Okuda, T, Asai, K: Fuzzy information and decision in a statistical model. In: Gupta, MM, et al (eds.)Advances in Fuzzy Set Theory and Applications, pp. 303–320. Amsterdam, North-Holland (1979). Torabi, H, Behboodian, J: Sequential probability ratio test for fuzzy hypotheses testing with vague data. Austrian J. Statistics. 34, 25–38 (2005). Viertl, R: Univariate statistical analysis with fuzzy data. Comput. Stat. Data Anal. 51, 133–147 (2006). Zadeh, LA: Probability measures of fuzzy events. J. Math. Anal. Appl. 23, 421–427 (1968). Zadeh, LA: Fuzzy sets. Inf. Control. 8, 338–359 (1965).