Estimation of Quantile Functionals in Linear Model

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Jurečková, Jana, Picek, Jan, Kalina, Jan
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866917629584736256
author Jurečková, Jana
Picek, Jan
Kalina, Jan
author_facet Jurečková, Jana
Picek, Jan
Kalina, Jan
contents Various indicators and measures of the real life procedures rise up as functionals of the quantile process of a parent random variable Z. However, Z can be observed only through a response in a linear model whose covariates are not under our control and the probability distribution of error terms is generally unknown. The problem is that of nonparametric estimation or other inference for such functionals. We propose an estimation procedure based on the averaged two-step regression quantile, recently developed by the authors, combined with an R-estimator of slopes of the linear model.
format Preprint
id arxiv_https___arxiv_org_abs_2404_02764
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Estimation of Quantile Functionals in Linear Model
Jurečková, Jana
Picek, Jan
Kalina, Jan
Methodology
62G05, 62J05
Various indicators and measures of the real life procedures rise up as functionals of the quantile process of a parent random variable Z. However, Z can be observed only through a response in a linear model whose covariates are not under our control and the probability distribution of error terms is generally unknown. The problem is that of nonparametric estimation or other inference for such functionals. We propose an estimation procedure based on the averaged two-step regression quantile, recently developed by the authors, combined with an R-estimator of slopes of the linear model.
title Estimation of Quantile Functionals in Linear Model
topic Methodology
62G05, 62J05
url https://arxiv.org/abs/2404.02764