GD.Biplot {MultBiplotR}

Biplot for continuous data based on gradient descent methods

Description

Biplot for continuous data based on gradient descent methods.

Usage

GD.Biplot(X, dimension = 2, Scaling = 5, 
         lambda = 0.01, OptimMethod = "CG", 
         Orthogonalize = FALSE, Algorithm = "Alternated", 
         sup.rows = NULL, sup.cols = NULL,
         grouping = NULL, tolerance = 1e-04, 
         num_max_iters = 300, Initial = "random")

Arguments

X

A data matrix with continuous variables.

dimension

Dimension of the final solution.

Scaling

Transformation of the raw data matrix before the calculation of the biplot.

lambda

Constant for the ridge Penalization

OptimMethod

Optimization method passed to the optim function. By default is CG (Conjugate Gradient).

Orthogonalize

Should the solution be ortogonalized.

Algorithm

Algorithm to calculate the Biplot. (Alternated, Joint, Recursive)

sup.rows

Supplementary Rows. (not working now)

sup.cols

Supplementary Columns. (not working now)

grouping

Grouping factor for the within groups transformation.

tolerance

Tolerance for convergence

num_max_iters

Maximum number of iterations.

Initial

Initial Configuration

Details

The function calculates a bilot using gradient descent methods. The function optim is used to optimize the loss function. By default CG (Conjugate Gradient) method is used althoug other possibilities can be used.

Value

An object of class "ContinuousBiplot" is returned.

Author(s)

Jose Luis Vicente Villardon

Examples

data("Protein")
X=Protein[,3:11]
gdbip=GD.Biplot(X, dimension=2, Algorithm="Joint", 
Orthogonalize=FALSE, lambda=0.3, Initial="random")
plot(gdbip)
summary(gdbip)