BinaryLogBiplotGD: Binary Logistic Biplot with Gradient Descent Estimation

Description Usage Arguments Details Value Author(s) References Examples

View source: R/BinaryLogBiplotGD.R

Description

Binary Logistic Biplot with Gradient Descent Estimation. An external optimization function is used to calculate the parameters.

Usage

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BinaryLogBiplotGD(X, freq = matrix(1, nrow(X), 1), dim = 2, tolerance =
                   1e-07, penalization = 0.01, num_max_iters = 100,
                   RotVarimax = FALSE, seed = 0, OptimMethod = "CG",
                   Initial = "random", Orthogonalize = FALSE, Algorithm =
                   "Joint", ...)

Arguments

X

A binary data matrix

freq

Frequencies of each row. When adequate.

dim

Dimension of the final solution.

tolerance

Tolerance for convergence of the algorithm.

penalization

Ridge penalization constant.

num_max_iters

Maximum number of iterations of the algorithm.

RotVarimax

Should the final solution be rotated.

seed

Seed for the random numbers. Used for reproductibility.

OptimMethod

Optimization method used by optimr.

Initial

Initial configuration to start the iterations.

Orthogonalize

Should te solution be orthogonalized?.

Algorithm

Algorithm for esimation: Joint or alternated.

...

Aditional parameters used by the optimization function.

Details

Fits a binary logistic biplot using gradient descent. The general function optimr is used to optimize the loss function. Conjugate gradien is used as a default although other alternatives can be USED.

Value

An object of class "Binary.Logistic.Biplot".

Author(s)

Jose Luis Vicente-Villardon

References

Vicente-Villardon, J. L., Galindo, M. P. and Blazquez, A. (2006) Logistic Biplots. In Multiple Correspondence AnĂ¡lisis And Related Methods. Grenacre, M & Blasius, J, Eds, Chapman and Hall, Boca Raton.

Demey, J., Vicente-Villardon, J. L., Galindo, M.P. AND Zambrano, A. (2008) Identifying Molecular Markers Associated With Classification Of Genotypes Using External Logistic Biplots. Bioinformatics, 24(24): 2832-2838.

Examples

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data(spiders)
X=Dataframe2BinaryMatrix(spiders)

logbip=BinaryLogBiplotGD(X,penalization=0.1)
plot(logbip, Mode="a")
summary(logbip)

MultBiplotR documentation built on April 6, 2021, 9:08 a.m.