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Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

Jibo Wu1

  • 1School of Mathematics and Finances, Chongqing University of Arts and Sciences, Chongqing, 402160 China ; Key Laboratory of Group & Graph Theories and Applications, Chongqing University of Arts and Sciences, Chongqing, 402160 China.

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This study introduces a new statistical method, the generalized difference-based ridge estimator, for analyzing dependent errors in partial linear models. The proposed estimator shows strong performance in simulations and examples.

Keywords:
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Area of Science:

  • Statistics
  • Econometrics

Background:

  • Partial linear models are widely used in statistical analysis.
  • Dependent errors can complicate parameter estimation in these models.

Purpose of the Study:

  • To propose a new generalized difference-based ridge estimator for vector parameters in partial linear models with dependent errors.
  • To compare the performance of the new estimator against existing methods.

Main Methods:

  • Developing a generalized difference-based ridge estimator.
  • Analyzing the mean-squared error matrix of the proposed estimator.
  • Comparing it with the generalized restricted difference-based estimator.

Main Results:

  • The proposed estimator is theoretically analyzed.
  • Simulation studies and a numerical example demonstrate its effectiveness.

Conclusions:

  • The new generalized difference-based ridge estimator is a viable and effective tool for analyzing partial linear models with dependent errors.
  • The findings provide valuable insights for statistical modeling in the presence of error dependencies.