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Bivariate linear hazard quantile distribution
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DOI：10.1080/03610926.2026.2663485.png)
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Abstract
En 中文
The development of new models using specialized forms of reliability functions has been a topic of interest among researchers for the past five decades. A significant amount of research also exists in the bivariate case, where various bivariate distributions have been constructed using different failure patterns. As far as bivariate quantile-based reliability analysis is concerned, research in this direction is in its early stages. In this paper, we propose a new distribution by assuming a linear form of quantile-based hazard gradients. This is a novel approach for developing bivariate distributions. We extensively study the properties and applications of this distribution and present several well-known bivariate distributions as members of this family. The marginal and joint density functions of the distribution exhibit various shapes, which enable it to model various types of bivariate lifetime data. The distributional characteristics based on ordinary moments and L-moments are analyzed, and the reliability properties of the distribution are examined. Despite being constructed using a linear form of quantile-based hazard gradients, the hazard gradients derived from the distribution function exhibit non-monotonic shapes, which further enhance the distribution's applicability in modeling bivariate data. The utility of the distribution in modeling is illustrated using real data examples.
Keywords:
Bivariate quantile function
quantile-based hazard gradients
bivariate mean residual function
bivariate linear hazard quantile distribution
L-moments
Journal
C
IF:
0.8
Papers:
211
Citations:
0