Title: Handling Missing Values with Multivariate Data Analysis
Description: 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.

Description: 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 or MCA.

analysis (PCA), a multiple correspondence analysis (MCA) model
or a multiple factor analysis (MFA) model; Perform multiple

Description: 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

Description: Supply functions for the creation and handling of missing data
as well as tools to evaluate missing data methods. Nearly all possibilities
of generating missing data discussed by Santos et. al (2019)
<doi:10.1109/ACCESS.2019.2891360> and some additional are implemented.
Functions are supplied to compare parameter estimates and imputed values to
true values to evaluate missing data methods. Evaluations of these types
are done, for example, by Cetin-Berber et al. (2019)
Suggests: ggplot2, knitr, lpSolve, rmarkdown, testthat (>= 2.1.0),

Description: Supply functions for the creation and handling of
missing data as well as tools to evaluate missing data methods. Nearly
all possibilities of generating missing data discussed by Santos et.
al (2019) <doi:10.1109/ACCESS.2019.2891360> and some additional are
implemented.  Functions are supplied to compare parameter estimates
and imputed values to true values to evaluate missing data methods.
Evaluations of these types are done, for example, by Cetin-Berber et
Suggests: ggplot2, knitr, lpSolve, mvtnorm, norm, rmarkdown, testthat