Abstract
This paper is devoted to the problems of testing statistical hypotheses about an experiment, when the available information from its sampling is `vague'. When the information supplied by the experimental sampling is exact, the problems of testing statistical hypotheses about the experiment can be regarded as a particular statistical decision problem. In addition, decision procedures may be used in problems of testing hypotheses. In a similar manner, the problem of testing statistical hypotheses about an experiment when the available sample information is vague, is approached in this paper as a particular fuzzy decision problem (as defined by Tanaka, Okuda and Asai). This approach assumes that the previous information about the experiment can be expressed by means of certain conditional probabilistic information, whereas the present information about it can be expressed by means of fuzzy information. The preceding framework allows us to extend the notion of risk function and some nonfuzzy decision procedures to the fuzzy case, and particularize them to the problem of testing. Finally, several illustrative examples are presented.
Published Version
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