International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 4 July-August 2024 Submit your research before last 3 days of August to publish your research paper in the issue of July-August.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 4
July-August 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Eliminate the Heterogeneous Variances Effect Using Quantile Regression

Author(s) Abdelbaset Abdalla, Wafa Omar El_khafifi, Ahmed M. Mami, Nasir Elmesmari
Country Libyan Arab Jamahiriya
Abstract Quantile regression (QR) is a statistical method that addresses the issue of inconsistent data errors. QR utilizes minimum absolute deviation to reduce the absolute deviation by employing percentile estimators such as the median, 1st and 3rd quartiles, and 10th and 90th percentiles. This study focuses on the qth percentile estimators of QR. QR models not only detect varying effects of explanatory variables at different quantiles of the response variable but also provide more robust and accurate estimates compared to mean regression when normality assumptions are violated or when outliers and long tails are present. This study conducts several simulation studies to compare the suggested qth percentile estimators of QR under different sample sizes, explanatory variables, and qth percentiles. Additionally, the study examines the impact of error terms dependency on normal/non-normal distribution. The asymptotic properties of these estimators are also investigated. The study concludes with a discussion of the advantages and disadvantages of using these qth percentile estimators of QR.
Keywords Heterogeneous Variances Effect; Variance Inflation Factor (VIF); Quantile Regression
Field Mathematics > Statistics
Published In Volume 5, Issue 5, September-October 2023
Published On 2023-10-27
Cite This Eliminate the Heterogeneous Variances Effect Using Quantile Regression - Abdelbaset Abdalla, Wafa Omar El_khafifi, Ahmed M. Mami, Nasir Elmesmari - IJFMR Volume 5, Issue 5, September-October 2023. DOI 10.36948/ijfmr.2023.v05i05.8013
DOI https://doi.org/10.36948/ijfmr.2023.v05i05.8013
Short DOI https://doi.org/gszvfj
View / Download PDF File

Share this


E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 3 Cover Page Vol 6 Isu 2 Cover Page Vol 6 Isu 1

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com