orange: Sensory description of 12 orange juices by 8 attributes.

In missMDA: Handling Missing Values with Multivariate Data Analysis

Description

Sensory description of 12 orange juices by 8 attributes. Some values are missing.

Usage

data(orange)

Format

A data frame with 12 rows and 8 columns. Rows represent the different orange juices, columns represent the attributes.

Details

A sensory data frame.

Source

Francois Husson, Agrocampus Rennes

Examples

## Not run: 
data(orange)
nb <- estim_ncpPCA(orange,ncp.min=0,ncp.max=5,method.cv="Kfold",nbsim=20,pNA=0.05)
res.comp <- imputePCA(orange,ncp=nb$ncp)
require(FactoMineR)
res.pca <- PCA(res.comp$completeObs)
resMI <- MIPCA(orange,ncp=nb$ncp)
plot(resMI)

## End(Not run)

Example output

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Warning messages:
1: In impute(X, ncp = ncp, scale = scale, method = method, threshold = threshold,  :
  Stopped after  1000  iterations
2: In impute(X, ncp = ncp, scale = scale, method = method, threshold = threshold,  :
  Stopped after  1000  iterations
3: In impute(X, ncp = ncp, scale = scale, method = method, threshold = threshold,  :
  Stopped after  1000  iterations
4: In impute(X, ncp = ncp, scale = scale, method = method, threshold = threshold,  :
  Stopped after  1000  iterations
5: In impute(X, ncp = ncp, scale = scale, method = method, threshold = threshold,  :
  Stopped after  1000  iterations
Loading required package: FactoMineR
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
dev.new(): using pdf(file="Rplots5.pdf")

missMDA documentation built on Dec. 15, 2020, 5:22 p.m.