Shrinkage estimation in spatial autoregressive model

DOI10.1016/J.JMVA.2015.09.011zbMath1328.62433OpenAlexW1763289728MaRDI QIDQ900819

Amresh Bahadur Pal, Anoop Chaturvedi, Ashutosh Kumar Dubey

Publication date: 23 December 2015

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2015.09.011

zbMATH Keywords

asymptotic distributionshrinkage estimationspatial modelquadratic loss functiondouble \(k\)-class estimatorminimum mean squared error estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (1)

Quantile regression for varying coefficient spatial error models

Uses Software

• R
• Arc_Mat

Cites Work

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• Selecting a double \(k\)-class estimator for regression coefficients
• Stein estimation -- a review
• Operational variants of the minimum mean squared error estimator in linear regression models with non-spherical disturbances
• Risk and Pitman closeness properties of feasible generalized double \(k\)-class estimators in linear regression models with non-spherical disturbances under balanced loss function
• On an adjustment of degrees of freedom in the minimim mean squared error ertimator
• Stein-rule estimation under an extended balanced loss function
• Double k-Class Estimators of Coefficients in Linear Regression
• Exact small sample properties of an operational variant of the minimum mean squared error estimator
• Double \(k\)-class estimators in regression models with non-spherical disturbances

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