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<p>This paper contains the proof of the asymptotic uniform linearity of a sequence of simple linear signed-rank statistics based on the residuals of a class of nonlinear parametric regression models, where regression errors are possibly dependent on the covariates. This result in turn is used to prove the asymptotic normality of a signed rank estimator of the regression parameter vector in the given nonlinear regression model where covariates and regression errors are dependent and in the errors in variables linear regression model, when the distributions of the covariates and measurement errors are known.</p>

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A signed-rank estimator for nonlinear regression models when covariates and errors are dependent

  • 期刊论文

  • 发表日期：

    2025年4月30日

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  • Hira L. Koul,
  • Palaniappan Vellaisamy

摘要

This paper contains the proof of the asymptotic uniform linearity of a sequence of simple linear signed-rank statistics based on the residuals of a class of nonlinear parametric regression models, where regression errors are possibly dependent on the covariates. This result in turn is used to prove the asymptotic normality of a signed rank estimator of the regression parameter vector in the given nonlinear regression model where covariates and regression errors are dependent and in the errors in variables linear regression model, when the distributions of the covariates and measurement errors are known.