Smooth residual bootstrap for empirical processes of non-parametric regression residuals

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Autor/in:
Erscheinungsjahr:
2009
Medientyp:
Text
Schlagworte:
  • Nonparametric regression
  • Goodness-of-fit test
  • Null distribution
  • Estimator
  • Models
  • Variable Selection
  • Nonparametric regression
  • Goodness-of-fit test
  • Null distribution
  • Estimator
  • Models
  • Variable Selection
Beschreibung:
  • The aim of this paper is to prove the validity of smooth residual bootstrap versions of procedures that are based on the empirical process of residuals estimated from a non-parametric regression model. From this result, consistency of various model tests in non-parametric regression is deduced, such as goodness-of-fit tests for the regression and variance function, tests for equality of regression functions and tests concerning the error distribution.
  • The aim of this paper is to prove the validity of smooth residual bootstrap versions of procedures that are based on the empirical process of residuals estimated from a non-parametric regression model. From this result, consistency of various model tests in non-parametric regression is deduced, such as goodness-of-fit tests for the regression and variance function, tests for equality of regression functions and tests concerning the error distribution. © 2009 Board of the Foundation of the Scandinavian Journal of Statistics.
Lizenz:
  • info:eu-repo/semantics/closedAccess
Quellsystem:
Forschungsinformationssystem der UHH

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oai:www.edit.fis.uni-hamburg.de:publications/da754dbd-5df7-4487-bfc3-3b92f4fa463a