Improved shrinkage estimators for the mean vector of a scale mixture of normals with unknown variance

DOI10.2307/3314730zbMath0678.62018OpenAlexW2035998413MaRDI QIDQ3834857

Gina Bravo, K. Brenda MacGibbon

Publication date: 1988

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3314730

zbMATH Keywords

unknown variancebalanced designscale mixturesmean estimationmixtures of normal distributionsJames-Stein estimatorsimproved shrinkage estimatorsminimax shrinkage estimators

Mathematics Subject Classification ID

Point estimation (62F10) Minimax procedures in statistical decision theory (62C20)

Related Items (3)

Improved estimators of a location vector with unknown scale parameter ⋮ James-stein estimation with constraints on the norm ⋮ Estimation of a scale parameter in mixture models with unknown location

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Selecting a minimax estimator of a multivariate normal mean
• Minimax estimators of the mean of a multivariate normal distribution
• Minimax estimation of location vectors for a wide class of densities
• Families of minimax estimators of the mean of a multivariate normal distribution
• Combining independent normal mean estimation problems with unknown variances
• Minimax estimation of a normal mean vector for arbitrary quadratic loss and unknown covariance matrix
• Minimax estimation of location parameters for certain spherically symmetric distributions
• Invariance, Minimax Sequential Estimation, and Continuous Time Processes
• Minimax Adaptive Generalized Ridge Regression Estimators
• Estimating the Mean of a Multivariate Normal Population with General Quadratic Loss Function

This page was built for publication: Improved shrinkage estimators for the mean vector of a scale mixture of normals with unknown variance