Similarity based one-sided tests for the expected value and interval data

DOI

10.2991/ifsa-eusflat-15.2015.135How to use a DOI?

Keywords

One-sided hypothesis test, expected value, interval data, hypothesis testing, bootstrap approach.

Abstract

A novel way for addressing one-sided hypothesis tests for the mean of unable to observe real random variables from which we have information provided in terms of interval data is proposed. For this purpose, a measure of similarity between intervals is considered and the classical one-sided hypothesis test to check whether the similarity between the expectation of a random interval and a subset of an specific unbounded interval is high enough. Asymptotic and bootstrap techniques are applied in order to study the limit distribution of the proposed test statistic. Some simulations have been carried out in order to show the empirical behavior of the test.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Przemyslaw Grzegorzewski
AU  - Ana Belén Ramos-Guajardo
PY  - 2015/06
DA  - 2015/06
TI  - Similarity based one-sided tests for the expected value and interval data
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 960
EP  - 966
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.135
DO  - 10.2991/ifsa-eusflat-15.2015.135
ID  - Grzegorzewski2015/06
ER  -