Progressive Type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution
El-Sayed A. El-Sherpieny,
Ehab M. Almetwally and
Hiba Z. Muhammed
Physica A: Statistical Mechanics and its Applications, 2020, vol. 553, issue C
Abstract:
In this paper, progressive Type-II hybrid censoring based on maximum product spacing method is introduced. Parameters estimation for the Power Lomax (PL) distribution are discussed under the progressive Type-II hybrid censoring based on maximum likelihood estimation and maximum product spacing method. A comparison studies with classical methods as maximum likelihood is discussed. Also, asymptotic confidence intervals and bootstrap confidence intervals are obtained. A numerical study using two real data and Monte Carlo simulation are performed to compare between the different methods.
Keywords: Power Lomax distribution; Progressive Type-II hybrid censoring; Maximum product spacing; Maximum likelihood and bootstrap confidence intervals (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120300662
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
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:eee:phsmap:v:553:y:2020:i:c:s0378437120300662
DOI: 10.1016/j.physa.2020.124251
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().