On the Performance of the Jackknifed Modified Ridge Estimator in the Linear Regression Model with Correlated or Heteroscedastic Errors
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Publication:3017876
DOI10.1080/03610926.2010.491589zbMath1216.62106OpenAlexW2172139680MaRDI QIDQ3017876
Publication date: 20 July 2011
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2010.491589
generalized least squares estimatejackknifed ridge estimatorgeneralized modified ridge estimatorjackknife procedure
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Cites Work
- A class of almost unbiased and efficient estimators of regression coefficients
- A jackknifed ridge estimator in the linear regression model with heteroscedastic or correlated errors
- A unified jackknife theory for empirical best prediction with \(M\)-estimation
- On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors
- NOTES ON BIAS IN ESTIMATION
- On the almost unbiased ridge regression estimator
- A Simulation Study of Ridge Regression Estimators with Autocorrelated Errors
- Some remarks on a ridge-type-estimator and good prior means
- On small sample properties of the almost unbiased generalized ridge estimator
- Good ridge estimators based on prior information
- Unnamed Item
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