Minimum mean-squared error estimation in linear regression with an inequality constraint
From MaRDI portal
Publication:1973322
DOI10.1016/S0378-3758(99)00172-XzbMath0964.62056MaRDI QIDQ1973322
Alan T. K. Wan, Kazuhiro Ohtani
Publication date: 14 December 2000
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Related Items
MSE Performance of a Heterogeneous Pre-Test Ridge Regression Estimator, Linear approximate Bayes estimator for regression parameter with an inequality constraint, Estimation of a subset of regression coefficients of interest in a model with non-spherical disturbances, Estimating the error variance after a pre-test for an interval restriction on the coefficients, Testing inequality constraints in a linear regression model with spherically symmetric disturbances
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Minimum mean square error estimation in linear regression
- Minimum mean squared error estimation of each individual coefficient in a linear regression model
- Generalized ridge regression estimators under the LINEX loss function
- The non-optimality of the inequality restricted estimator under squared error loss
- The exact risks of some pre-test and stein-type regression estimators umder balanced loss
- On an adjustment of degrees of freedom in the minimim mean squared error ertimator
- The Minimum Mean Square Error Linear Estimator and Ridge Regression
- Simulation and Extension of a Minimum Mean Squared Error Estimator in Comparison with Stein's
- On the minimum mean squared error estimators in a regression model
- Risk Comparison of Inequality Constrained Estimators in the Heteroscedastic Linear Model
- On the Sampling Performance of an Improved Stein Inequality Restricted Estimator
- Exact small sample properties of an operational variant of the minimum mean squared error estimator
- THE SAMPLING PERFORMANCE OF INEQUALITY RESTRICTED AND PRE‐TEST ESTIMATORS IN A MIS‐SPECIFIED LINEAR MODEL
- A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution