A note on an approximation and estimation of distribution function of difference of random variables

Abstract In this paper we deal with the problem of determining the distribution function of the difference of two independent random variables. Using a quantile-based representation we obtain an approximation of distribution function of difference of two independent random variables. Next, we obtain the error of this approximation. Finally, we use the approximation to present a non-parametric estimator for the distribution function of difference of two independent random variables. Moreover, we prove the strong consistency of this estimator and we carry out a numerical simulation to evaluate the bias and mean squared error of the estimator. Also we compare our estimator with the classical empirical distribution function.

Authors

Institutions

Publication Details

Journal
Statistical Papers
Published
2025-11-20
DOI
https://doi.org/10.1007/s00362-025-01776-w
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A note on an approximation and estimation of distribution function of difference of random variables

Dagmara Dudek, Anna Kuczmaszewska
Statistical Papers
Statistical Distribution Estimation and Applications
article

A note on an approximation and estimation of distribution function of difference of random variables

Dagmara Dudek, Anna Kuczmaszewska
article en

Abstract

Abstract In this paper we deal with the problem of determining the distribution function of the difference of two independent random variables. Using a quantile-based representation we obtain an approximation of distribution function of difference of two independent random variables. Next, we obtain the error of this approximation. Finally, we use the approximation to present a non-parametric estimator for the distribution function of difference of two independent random variables. Moreover, we prove the strong consistency of this estimator and we carry out a numerical simulation to evaluate the bias and mean squared error of the estimator. Also we compare our estimator with the classical empirical distribution function.

Statistical PapersVol. 66(7)
Lublin University of Technology (PL)
Openalex Percentile: Top 67%
Statistical Distribution Estimation and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A note on an approximation and estimation of distribution function of difference of random variables — Dagmara Dudek, Anna Kuczmaszewska · Statistical Papers (2025) | TGRS Research Map | TGRS