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• W2980158862 abstract "Testing for series correlation among error terms is a basic problem in linear regression model diagnostics. The famous Durbin-Watson test and Durbin's h-test rely on certain model assumptions about the response and regressor variables. The present paper proposes simple tests for series correlation that are applicable in both fixed and random design linear regression models. The test statistics are based on the regression residuals and design matrix. The test procedures are robust under different distributions of random errors. The asymptotic distributions of the proposed statistics are derived via a newly established joint central limit theorem for several general quadratic forms and the delta method. Good performance of the proposed tests is demonstrated by simulation results." @default.
• W2980158862 created "2019-10-18" @default.
• W2980158862 creator A5034023112 @default.
• W2980158862 date "2020-05-01" @default.
• W2980158862 modified "2023-09-27" @default.
• W2980158862 title "Model-free tests for series correlation in multivariate linear regression" @default.
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• W2980158862 doi "https://doi.org/10.1016/j.jspi.2019.09.011" @default.
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