Interval-valued observations arise in several real-life situations, and it is convenient to develop statistical methods to deal with them. In the literature on Statistical Inference with single-valued observations one can find different studies on drawing conclusions about the population mean on the basis of the information supplied by the available observations. In this paper we present a bootstrap method of testing a 'two-sided' hypothesis about the (interval-valued) mean value of an interval-valued random set based on an extension of the t statistic for single-valued data. The method is illustrated by means of a real-life example. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Montenegro, M., Casals, M. R., Colubi, A., & Gil, M. Á. (2008). Testing “two-sided” hypothesis about the mean of an interval-valued random set. Advances in Soft Computing, 48, 133–139. https://doi.org/10.1007/978-3-540-85027-4_17
Mendeley helps you to discover research relevant for your work.