A time-discrete and zero-adjusted gamma process model with application to degradation analysis

Kai Song, Jian Shi and Xiaojian Yi

Physica A: Statistical Mechanics and its Applications, 2020, vol. 560, issue C

Abstract: The standard gamma process is widely used for degradation modelling when the degradation paths are always positive and strictly increasing. Nevertheless, the standard gamma process is considered inappropriate if the observed sample paths are horizontal over several time intervals. Motivated by this phenomenon, we develop a time-discrete and zero-adjusted gamma process model. Statistical inference method of this model is then proposed. To illustrate our proposed model, both simulation study and real data analysis are conducted, whose results demonstrate that the proposed model has satisfactory fit performance and predictive performance.

Keywords: Gamma process; Zero-adjusted; Time-discrete; Goodness-of-fit; Predictive performance (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120306166
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:560:y:2020:i:c:s0378437120306166

DOI: 10.1016/j.physa.2020.125180

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 ().