Ridge Estimation in Linear Models with Autocorrelated Errors

DOI10.1080/03610920903075435zbMath1204.62122OpenAlexW2058155768MaRDI QIDQ2786250

M. A. Alkhamisi

Publication date: 21 September 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920903075435

zbMATH Keywords

Monte Carlo simulationridge regressionautocorrelationmulticollinearityLiu estimatorSarkar estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Parametric inference under constraints (62F30) Monte Carlo methods (65C05)

Related Items (4)

Ridge estimation in linear models with heteroskedastic errors ⋮ Recent results in ridge regression methods ⋮ A note on the performance of biased estimators with autocorrelated errors ⋮ A Combined Nonlinear Programming Model and Kibria Method for Choosing Ridge Parameter Regression

Cites Work

• Unnamed Item
• Unnamed Item
• A Monte Carlo Study of Recent Ridge Parameters
• A Simulation Study of Ridge Regression Estimators with Autocorrelated Errors
• Bayesian analysis of a linear mixed model with AR(p) errors via MCMC
• Generalized mean squared error comparisons of biased regression estimators
• A new estimator combining the ridge regression and the restricted least squares methods of estimation
• A new class of blased estimate in linear regression
• Superiority comparisons of homogeneous linear estimators
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Ridge Regression: Applications to Nonorthogonal Problems
• Linear Statistical Inference and its Applications

This page was built for publication: Ridge Estimation in Linear Models with Autocorrelated Errors