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

Lili Yue, Jianhong Shi, Jingxuan Luo and Jinguan Lin ()
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Lili Yue: School of Statistics and Data Science, Nanjing Audit University, Nanjing 211815, China
Jianhong Shi: School of Mathematics and Computer Science, Shanxi Normal University, Taiyuan 030032, China
Jingxuan Luo: School of Statistics, Beijing Normal University, Beijing 100875, China
Jinguan Lin: School of Statistics and Data Science, Nanjing Audit University, Nanjing 211815, China

Mathematics, 2023, vol. 11, issue 19, 1-13

Abstract: 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.

Keywords: parametric bootstrap; one-way error component regression model; measurement errors; hypothesis test (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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