MultBiplotR (version 23.11.0)

NIPALS.Biplot: Biplot using the NIPALS algorithm

Description

Biplot using the NIPALS algorithm including a truncated and a sparse version.

Usage

NIPALS.Biplot(X, alpha = 1, dimension = 3, Scaling = 5, 
Type = "Regular", grouping = NULL, ...)

Value

An object of class ContinuousBiplot with the following components:

Title

A general title

Type

NIPALS

call

call

Non_Scaled_Data

Original Data Matrix

Means

Means of the original Variables

Medians

Medians of the original Variables

Deviations

Standard Deviations of the original Variables

Minima

Minima of the original Variables

Maxima

Maxima of the original Variables

P25

25 Percentile of the original Variables

P75

75 Percentile of the original Variables

Gmean

Global mean of the complete matrix

Sup.Rows

Supplementary rows (Non Transformed)

Sup.Cols

Supplementary columns (Non Transformed)

Scaled_Data

Transformed Data

Scaled_Sup.Rows

Supplementary rows (Transformed)

Scaled_Sup.Cols

Supplementary columns (Transformed)

n

Number of Rows

p

Number of Columns

nrowsSup

Number of Supplementary Rows

ncolsSup

Number of Supplementary Columns

dim

Dimension of the Biplot

EigenValues

Eigenvalues

Inertia

Explained variance (Inertia)

CumInertia

Cumulative Explained variance (Inertia)

EV

EigenVectors

Structure

Correlations of the Principal Components and the Variables

RowCoordinates

Coordinates for the rows, including the supplementary

ColCoordinates

Coordinates for the columns, including the supplementary

RowContributions

Contributions for the rows, including the supplementary

ColContributions

Contributions for the columns, including the supplementary

Scale_Factor

Scale factor for the traditional plot with points and arrows. The row coordinates are multiplied and the column coordinates divided by that scale factor. The look of the plot is better without changing the inner product. For the HJ-Biplot the scale factor is 1.

Arguments

X

The data matrix

alpha

A number between 0 and 1. 0 for GH-Biplot, 1 for JK-Biplot and 0.5 for SQRT-Biplot. Use 2 or any other value not in the interval [0,1] for HJ-Biplot.

dimension

Dimension of the solution

Scaling

Transformation of the original data. See InitialTransform for available transformations.

Type

Type of biplot (Regular, Truncated or Sparse)

grouping

Grouping fartor when the scaling is made with the within groups variability

...

Aditional arguments for the different types of biplots.

Author

Jose Luis Vicente Villardon

Details

Biplot using the NIPALS algorithm including a truncated and a sparse version.

References

Wold, H. (1966). Estimation of principal components and related models by iterative least squares. Multivariate analysis. ACEDEMIC PRESS. 391-420.

Examples

bip1=NIPALS.Biplot(wine[,4:21], Type="Sparse", lambda=0.15)
plot(bip1)