Article ID Journal Published Year Pages File Type
393322 Information Sciences 2014 11 Pages PDF
Abstract

An extension of the inclusion test of the expected value of a real random variable in an interval to the case of general random intervals is introduced. The hypothesis of strict inclusion is relaxed by considering a measure of the degree of inclusion. Thus, partial inclusions are also tested. Asymptotic and bootstrap techniques are established. The performance of the bootstrap test is also analyzed by means of some simulations. A case-study regarding the blood pressure classification in adults is considered.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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