A new class of bivariate lifetime distributions

No Thumbnail Available

Date

2017

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis inc

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Organizational Units

Thumbnail Image
Organizational Unit
Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

Journal Issue

Abstract

This paper introduces a new class of bivariate lifetime distributions. Let {X-i}(i 1) and {Y-i}(i 1) be two independent sequences of independent and identically distributed positive valued random variables. Define T-1 = min(X-1, ..., X-M) and T-2 = min(Y-1, ..., Y-N), where (M, N) has a discrete bivariate phase-type distribution, independent of {X-i}(i 1) and {Y-i}(i 1). The joint survival function of (T-1, T-2) is studied.

Description

Eryilmaz, Serkan/0000-0002-2108-1781
ORCID
Eryilmaz, Serkan ORCID logo

Keywords

Bivariate geometric distribution, bivariate phase-type distributions, survival function

Turkish CoHE Thesis Center URL

Fields of Science

Citation

3

WoS Q

Q4

Scopus Q

Source

Volume

46

Issue

24

Start Page

12324

End Page

12335

URI

https://doi.org/10.1080/03610926.2017.1295078
 https://hdl.handle.net/20.500.14411/1621

Collections

WOS
Load more