A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors
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 coeff...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/11/19/4165 |
| Summary: | 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. |
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| ISSN: | 2227-7390 |