Nearest neighbours in least-squares data imputation algorithms with different missing patterns

DOI10.1016/j.csda.2004.11.009zbMath1431.62044OpenAlexW2145679125MaRDI QIDQ2257590

Ito Wasito, Boris G. Mirkin

Publication date: 25 February 2015

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://eprints.bbk.ac.uk/id/eprint/313/1/Binder1.pdf

zbMATH Keywords

singular value decompositionleast squaresmissing datanearest neighboursmerged database missingrandom missingrestricted random missing

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Point estimation (62F10) Missing data (62D10)

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Uses Software

• MULTIMIX
• impute

Cites Work

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• Weighted least squares fitting using ordinary least squares algorithms
• Regression-based nearest neighbour hot decking
• Nearest neighbour approach in the least-squares data imputation algorithms
• Mathematical classification and clustering
• Multiple Imputation After 18+ Years
• Lower Rank Approximation of Matrices by Least Squares with Any Choice of Weights
• Probabilistic Principal Component Analysis
• Using Linear Algebra for Intelligent Information Retrieval

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