Testing Heteroskedasticity in High‐Dimensional Linear Regression

Akira Shinkyu

doi:10.1016/j.ecosta.2023.10.003

ScienceGate Book Chapters

JOURNAL ARTICLE

Testing Heteroskedasticity in High‐Dimensional Linear Regression

Akira Shinkyu

Year: 2023 Journal: Econometrics and Statistics Vol: 35 Pages: 120-134 Publisher: Elsevier BV

DOI: 10.1016/j.ecosta.2023.10.003

Get Full-Text PDF Get Analytical Report

Keywords:

Homoscedasticity Heteroscedasticity Test statistic Covariate Statistics Mathematics Linear regression Null (SQL) Econometrics Sample size determination Linear model Asymptotic distribution Null hypothesis Lasso (programming language) Statistical hypothesis testing Statistic Applied mathematics Computer science Data mining Estimator

Metrics

Cited By

1.28

FWCI (Field Weighted Citation Impact)

Refs

0.74

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Testing Heteroskedasticity in High‐Dimensional Linear Regression

Metrics

Citation History

Topics

Related Documents

Testing for Heteroskedasticity and Predictive Failure in Linear Regression Models*

Testing high-dimensional regression coefficients in linear models

Optimal heteroskedasticity testing in nonparametric regression

Testing Overidentifying Restrictions with High-Dimensional Data and Heteroskedasticity

Testing a single regression coefficient in high dimensional linear models