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2021•American Journal of Mathematical and Management SciencesRequires access

Properties of Bivariate Distributions Represented through Quantile Functions

N. Unnikrishnan Nair, B. Vineshkumar

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Abstract

Recently, Vineshkumar and Nair (2019) have discussed the applications of bivariate quantile functions in the context of reliability analysis. But, the general properties of bivariate quantile functions have not been considered in their work. In the present paper, we carry out a preliminary study on the properties of bivariate distributions represented through quantile functions. The uses of the new results are illustrated in the case of a bivariate quantile function model by deriving their properties and then applying them to real data.

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What this paper is about

Recently, Vineshkumar and Nair (2019) have discussed the applications of bivariate quantile functions in the context of reliability analysis. But, the general properties of bivariate quantile functions have not been considered in their work. In the present paper, we carry out a preliminary study on the properties of bivariate distributions represented through quantile functions. The uses of the new results are illustrated in the case of a bivariate quantile function model by deriving their properties and then applying them to real data.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Recently, Vineshkumar and Nair (2019) have discussed the applications of bivariate quantile functions in the context of reliability analysis. But, the general properties of bivariate quantile functions have not been considered in their work. In the present paper, we carry out a preliminary study on the properties of bivariate distributions represented through quantile functions. The uses of the new results are illustrated in the case of a bivariate quantile function model by deriving their properties and then applying them to real data.

Key concepts: Quantile, Bivariate analysis, Bivariate data, Mathematics, Quantile function, Context (archaeology), Reliability (semiconductor), Econometrics

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