Neyman–Pearson lemma based on intuitionistic fuzzy parameters
作者： Mohammad Ghasem Akbari , Gholamreza Hesamian
DOI: 10.1007/S00500-018-3252-4
关键词:
摘要: The present work aims to extend the classical Neyman–Pearson lemma based on a random sample of exact observations test intuitionistic fuzzy hypotheses. In this approach, we concepts type-I error, type-II and power test. Some applied examples are provided illustrate proposed method. addition, method is examined be compared with an existing
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sci-hub.se 参考文章(50)
Pei-Chun Lin, Berlin Wu, Junzo Watada, Kolmogorov-Smirnov Two Sample Test with Continuous Fuzzy Data IUM. pp. 175- 186 ,(2010) , 10.1007/978-3-642-11960-6_17
Berlin Wu, Hung T. Nguyen, Fundamentals of Statistics with Fuzzy Data ,(2006)
K. H. Lee, First Course on Fuzzy Theory and Applications ,(2004)
Przemyslaw Grzegorzewski, Two-Sample Median Test for Vague Data. european society for fuzzy logic and technology conference. pp. 621- 626 ,(2005)
M. Arefi, Seed Mahmood Taheri, Testing fuzzy hypotheses using fuzzy data based on fuzzy test statistic Journal of Uncertain Systems. ,vol. 5, ,(2011)
Przemyslaw Grzegorzewski, None, Distribution-Free Tests for Vague Data Springer Berlin Heidelberg. pp. 495- 502 ,(2004) , 10.1007/978-3-540-44465-7_61
E. Szmidt, J. Kacprzyk, Using intuitionistic fuzzy sets in group decision making Control and Cybernetics. ,vol. 31, pp. 1055- 1057 ,(2002)
Reinhard Viertl, Statistical Methods for Fuzzy Data ,(2011)
P. Grzegorzewski, Statistical inference about the median from vague data Control and Cybernetics. ,vol. 27, pp. 447- 464 ,(1998)
Rudolf Kruse, Klaus Dieter Meyer, Statistics with vague data ,(1987)