TY - JOUR
AU1 - Sadeghpour-Gildeh, Bahram
AU2 - Rahimpour, Sedigheh
AB - AbstractIn this paper, we consider the problem of testing a simple hypothesis about the mean of a fuzzy random variable. For this purpose, we take a distance between the sample mean and the mean in the null hypothesis as a test statistic. An asymptotic test about the fuzzy mean is obtained by using a central limit theorem. The asymptotical distribution is ω2-distribution. The ω2-distribution is only known for special cases, thus we have considered random LR-fuzzy numbers. In the fuzzy concept, in addition to the existence of several versions of the central limit theorem, there is another practical disadvantage: The limit law is, in most cases, difficult to handle. Therefore, the central limit theorem for fuzzy random variable does not seem to be a very useful tool to make inferences on the mean of fuzzy random variable. Thus we use the bootstrap technique. Finally, by means of a simulation study, we show that the bootstrap method is a powerful tool in the statistical hypothesis testing about the mean of fuzzy random variables.
TI - A Fuzzy Bootstrap Test for the Mean with Dp, q-distance
JF - Fuzzy Information and Engineering
DO - 10.1007/s12543-011-0090-9
DA - 2011-12-01
UR - https://www.deepdyve.com/lp/taylor-francis/a-fuzzy-bootstrap-test-for-the-mean-with-dp-q-distance-UFHm3KsXw4
SP - 351
EP - 358
VL - 3
IS - 4
DP - DeepDyve
ER -