Quantiles play a fundamental role in statistics. The quantile function defines the distribution of a random variable and, thus, provides a way to describe the data that is specular but equivalent to that given by the corresponding cumulative distribution function. There are many advantages in working with quantiles, starting from their properties. The renewed interest in their usage seen in the last years is due to the theoretical, methodological, and software contributions that have broadened their applicability. This paper presents the R package Qtools , a collection of utilities for unconditional and conditional quantiles.

Qtools: A collection of models and tools for quantile inference / Geraci, M. - In: THE R JOURNAL. - ISSN 2073-4859. - 8:2(2016), pp. 117-138.

Qtools: A collection of models and tools for quantile inference

GERACI M
2016

Abstract

Quantiles play a fundamental role in statistics. The quantile function defines the distribution of a random variable and, thus, provides a way to describe the data that is specular but equivalent to that given by the corresponding cumulative distribution function. There are many advantages in working with quantiles, starting from their properties. The renewed interest in their usage seen in the last years is due to the theoretical, methodological, and software contributions that have broadened their applicability. This paper presents the R package Qtools , a collection of utilities for unconditional and conditional quantiles.
2016
bounded variables; discrete variables; multiple imputation; quantiles; transformation
01 Pubblicazione su rivista::01a Articolo in rivista
Qtools: A collection of models and tools for quantile inference / Geraci, M. - In: THE R JOURNAL. - ISSN 2073-4859. - 8:2(2016), pp. 117-138.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1463848
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