Relative squared error prediction in the generalized linear regression model
From MaRDI portal
Publication:1871692
DOI10.1007/s00362-002-0136-5zbMath1026.62072OpenAlexW2016552468MaRDI QIDQ1871692
Bernhard F. Arnold, Peter Stahlecker
Publication date: 4 May 2003
Published in: Statistical Papers (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00362-002-0136-5
Related Items (4)
Nonparametric relative error regression for spatial random variables ⋮ Minimax prediction in the linear model with a relative squared error ⋮ Some properties of the relative squared error approach to linear regression analysis ⋮ On two correlated linear models with common and different parameters
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Minimax estimation in linear regression with singular covariance structure and convex polyhedral constraints
- Some properties of \([tr(Q^{2p})^{1/2p}\) with application to linear minimax estimation]
- Minimax linear regression estimation with symmetric parameter restrictions
- Another view of the Kuks-Olman estimator
- Linear models. Least squares and alternatives
- Characterization of minimax linear estimators in linear regression
- Estimation and prediction for linear models in general spaces
- A minimax linear estimator for linear parameters under restrictions in form of inequalities
- Bayes, Admissible, and Minimax Linear Estimators in Linear Models with Restricted Parameter Space
- Minimax estimators for linear models with nonrandom disturbances
- Best Linear Unbiased Prediction in the Generalized Linear Regression Model
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
This page was built for publication: Relative squared error prediction in the generalized linear regression model
