دورية أكاديمية

A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors

التفاصيل البيبلوغرافية
العنوان: A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors
المؤلفون: Lili Yue, Jianhong Shi, Jingxuan Luo, Jinguan Lin
المصدر: Mathematics, Vol 11, Iss 19, p 4165 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Mathematics
مصطلحات موضوعية: parametric bootstrap, one-way error component regression model, measurement errors, hypothesis test, Mathematics, QA1-939
الوصف: In this paper, a one-way error component regression model with measurement errors is considered. The unknown parameter vector is estimated by using the bias-corrected method, and its corresponding asymptotic properties are also developed. For the hypothesis testing problem of the vector of the coefficient parameter in the model, a parametric bootstrap (PB) method is proposed. Under various sample sizes and parameter configurations, the effectiveness of our proposed PB test method is discussed by using some numerical simulations and a real data analysis.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2227-7390
Relation: https://www.mdpi.com/2227-7390/11/19/4165; https://doaj.org/toc/2227-7390
DOI: 10.3390/math11194165
URL الوصول: https://doaj.org/article/5373b43117624109b4c341107dc357f1
رقم الأكسشن: edsdoj.5373b43117624109b4c341107dc357f1
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22277390
DOI:10.3390/math11194165