missMDA: Handling missing values with/in multivariate data analysis (principal component methods)

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Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA

Author
Francois Husson, Julie Josse
Date of publication
None
Maintainer
Francois Husson <husson@agrocampus-ouest.fr>, Julie Josse <josse@agrocampus-ouest.fr>
License
GPL (>= 2)
Version
1.3
URLs

View on R-Forge

Man pages

estim_ncpMCA
Estimate the number of dimensions for the Multiple...
estim_ncpPCA
Estimate the number of dimensions for the Principal Component...
imputeMCA
Impute missing values in categorical variables with Multiple...
imputeMFA
Impute dataset with MFA
imputePCA
Impute dataset with PCA
MIPCA
Multiple Imputation with PCA
orange
Sensory description of 12 orange juices by 8 attributes.
plot.MIPCA
Plot the graphs for the Multiple Imputation in PCA
vnf
Questionnaire done by 1232 individuals who answered 14...

Files in this package

missMDA
missMDA/data
missMDA/data/orange.rda
missMDA/data/vnf.rda
missMDA/R
missMDA/R/imputePCA.R
missMDA/R/plot.MIPCA.R
missMDA/R/imputeMFA.R
missMDA/R/MIPCA.R
missMDA/R/estim_ncpPCA.R
missMDA/R/estim_ncpMCA.R
missMDA/R/imputeMCA.R
missMDA/NAMESPACE
missMDA/DESCRIPTION
missMDA/man
missMDA/man/MIPCA.Rd
missMDA/man/plot.MIPCA.Rd
missMDA/man/orange.Rd
missMDA/man/imputeMFA.Rd
missMDA/man/imputeMCA.Rd
missMDA/man/vnf.Rd
missMDA/man/imputePCA.Rd
missMDA/man/estim_ncpPCA.Rd
missMDA/man/estim_ncpMCA.Rd