A note on the performance of biased estimators with autocorrelated errors
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Publication:1751508
DOI10.1155/2017/2045653zbMath1476.62154DBLPjournals/ijmmsc/TyagiC17OpenAlexW2582941091WikidataQ59144848 ScholiaQ59144848MaRDI QIDQ1751508
Publication date: 25 May 2018
Published in: International Journal of Mathematics and Mathematical Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2017/2045653
Cites Work
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- A restricted \(r\)-\(k\) class estimator in the mixed regression model with autocorrelated disturbances
- The effects of the proxy information on the iterative Stein-rule estimator of the disturbance variance
- \(r\)-\(k\) class estimator in the linear regression model with correlated errors
- Inadmissibility of the iterative Stein-rule estimator of the disturbance variance in a linear regression
- Combining two-parameter and principal component regression estimators
- On a principal component two-parameter estimator in linear model with autocorrelated errors
- On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors
- Ridge Estimation in Linear Models with Autocorrelated Errors
- Estimation in Singular Linear Models with Stochastic Linear Restrictions and Linear Equality Restrictions
- A Simulation Study of Ridge Regression Estimators with Autocorrelated Errors
- A New Two-Parameter Estimator in Linear Regression
- A Comparison of Mixed and Ridge Estimators of Linear Models
- A Simulation Study of Some Ridge Estimators
- Ridge regression:some simulations
- A Monte Carlo Evaluation of Some Ridge-Type Estimators
- Simultaneous prediction intervals for all distances from the “best”
- COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
- Performance of Some New Ridge Regression Estimators
- IV.—On Least Squares and Linear Combination of Observations
- Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators
- Principal components regression estimator and a test for the restrictions
- The Restricted and Unrestricted Two-Parameter Estimators
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Ridge Regression: Applications to Nonorthogonal Problems
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