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This chapter focuses on the effects of correlated errors in linear regression, establishing parameter convergence conditions to ensure the consistency and asymptotic normality of covariance estimators. These results are further extended to nonlinear regression models, where asymptotic properties and confidence interval construction are explored.

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Fixed-Parameter Prototype Regression Models

  • 章节

  • 发表日期：

    2026年

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  • Asaf Hajiyev,
  • Jiuping Xu

摘要

This chapter focuses on the effects of correlated errors in linear regression, establishing parameter convergence conditions to ensure the consistency and asymptotic normality of covariance estimators. These results are further extended to nonlinear regression models, where asymptotic properties and confidence interval construction are explored.