sdv_MM: Fitting a Binary Logistic Biplot using coordinate descendent...

In jgbabativam/BiplotML: Biplots Estimation with Algorithms ML

Fitting a Binary Logistic Biplot using coordinate descendent MM algorithm

Description

This function estimates the vector μ, matrix A and matrix B using coordinate descendent MM algorithm.

Usage

sdv_MM(
  x,
  k = 2,
  iterations = 1000,
  truncated = TRUE,
  random = FALSE,
  epsilon = 1e-04
)

Arguments

x	binary matrix.
k	dimensions number. By default k = 2.
iterations	maximum iterations.
truncated	if TRUE, find the k largest singular values and vectors of a matrix.
random	random initialization
epsilon	convergence criteria

Value

Coordenates of the matrix A and B, and μ

Author(s)

Giovany Babativa <[e-mail]>

References

Babativa-Marquez, J. G., & Vicente-Villardon, J. L. (2021). Logistic Biplot by Conjugate Gradient Algorithms and Iterated SVD. Mathematics, 9(16).

Vicente-Villardon, J.L. and Galindo, M. Purificacion (2006), Multiple Correspondence Analysis and related Methods. Chapter: Logistic Biplots. Chapman-Hall

See Also

cv_LogBip

Examples

data("Methylation")
out <- sdv_MM(x = Methylation)

jgbabativam/BiplotML documentation built on July 31, 2022, 11:10 a.m.