Bootstrap approach to the multi-sample test of means with imprecise data
A bootstrap approach to the multi-sample test of means for imprecisely valued sample data is introduced. For this purpose imprecise data are modelled in terms of fuzzy values. Populations are identified with fuzzy-valued random elements, often referred to in the literature as fuzzy random variables. An example illustrates the use of the suggested method. Finally, the adequacy of the bootstrap approach to test the multi-sample hypothesis of means is discussed through a simulation comparative study. (C) 2006 Elsevier B.V. All rights reserved.
bootstrap fuzzy values fuzzy random variables one-way anova test large sample theory (w, phi)-metric