Tolerance Interval for the Mixture Normal Distribution Based on Generalized Extreme Value Theory

Junjun Jiao () and Ruijie Guan
Additional contact information
Junjun Jiao: School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China
Ruijie Guan: School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing 100124, China

Mathematics, 2024, vol. 12, issue 7, 1-11

Abstract: For a common type of mixture distribution, namely the mixture normal distribution, existing methods for constructing its tolerance interval are unsatisfactory for cases of small sample size and large content. In this study, we propose a method to construct a tolerance interval for the mixture normal distribution based on the generalized extreme value theory. The proposed method is implemented on simulated as well as real-life datasets and its performance is compared with the existing methods.

Keywords: tolerance interval; mixture normal distribution; the generalized extreme value theory; Gumbel distribution; the domain of maximal attraction (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/7/1114/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/7/1114/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:7:p:1114-:d:1371903

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().