missMDA: A Package for Handling Missing Values in Multivariate Data Analysis

missMDA: A Package for Handling Missing Values in Multivariate Data Analysis

We present the R package missMDA which performs principal component methods on incomplete data sets, aiming to obtain scores, loadings and graphical representations despite missing values. Package methods include principal component analysis for continuous variables, multiple correspondence analysis...

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Bibliographic Details
Main Authors: Julie Josse, François Husson
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2016-04-01
Series:Journal of Statistical Software
Subjects:
missing values
principal component analysis
single imputation
multiple imputation
multi-table data
mixed data
multiple correspondence analysis
multiple factor analysis
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/2615

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https://www.jstatsoft.org/index.php/jss/article/view/2615

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