An asymptotic minimax risk bound for estimation of a linear functional relationship

DOI10.1016/0047-259X(84)90035-6zbMath0538.62062MaRDI QIDQ793479

Michael Nussbaum

Publication date: 1984

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

zbMATH Keywords

convergence ratemaximum likelihood estimatorasymptotic minimax risknormal approximationlinear functional relationshiplocally asymptotically minimaxlower bound for the error probabilitymodel with errors in both variables

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (4)

Generalized least squares estimation of the functional multivariate linear errors-in-variables model ⋮ On a consistent rank estimate in a linear structural model ⋮ Statistically-based approach for monitoring of micro-seismic events ⋮ The efficiency of adjusted least squares in the linear functional relationship.

Cites Work

• The estimation of a multivariate linear relation
• On the validity of the formal Edgeworth expansion
• Matrix derivatives with an application to an adaptive linear decision problem
• Consistent estimation in the presence of incidental parameters
• Estimating structural and functional relationships
• Asymptotic efficiency of estimators of a multivariate linear functional relation¹
• Asymptotic minimax theorems for the sample distribution function
• Linear Statistical Inference and its Applications
• Consistent Estimates Based on Partially Consistent Observations
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