Imputation for skewed data: multivariate Lomax case

DOI10.1007/s13571-021-00251-4zbMath1471.62358OpenAlexW3131467090MaRDI QIDQ2047379

Zhixin Lun, Ravindra Khattree

Publication date: 19 August 2021

Published in: Sankhyā. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13571-021-00251-4

zbMATH Keywords

imputationmissing dataEM methodskewed datamultivariate Lomax distributioncopula transformation\(k\)-nearest-neighbor

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Inference from stochastic processes and prediction (62M20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Missing data (62D10)

Uses Software

• R
• norm
• VIM
• impute
• NonNorMvtDist

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Some prediction procedures with special reference to selection
• The Bivariate Normal Copula
• Imputing continuous data under some non‐Gaussian distributions
• Fully conditional specification in multivariate imputation
• Multivariate distributions for the life lengths of components of a system sharing a common environment
• Multivariate Lomax distribution: properties and usefulness in reliability theory
• Imputation in High-Dimensional Economic Data as Applied to the Agricultural Resource Management Survey
• Multiple imputation using multivariateghtransformations
• Business Failures: Another Example of the Analysis of Failure Data

This page was built for publication: Imputation for skewed data: multivariate Lomax case