Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/Ridge_HJBiplot.R
This function performs the representation of the HJ Biplot applying the Ridge regularization, on the original data matrix, implementing the norm L2.
1 | Ridge_HJBiplot (X, Lambda, Transform.Data = 'scale')
|
X |
array_like; |
Lambda |
float; |
Transform.Data |
character; |
Algorithm used to contract the loads of the main components towards zero, but without achieving the nullity of any. If the penalty parameter is less than or equal to 1e-4 the result is like Galindo's HJ Biplot (1986).
Ridge_HJBiplot
returns a list containing the following components:
eigenvalues |
array_like; |
explvar |
array_like; |
loadings |
array_like; |
coord_ind |
array_like; |
coord_var |
array_like; |
Mitzi Cubilla-Montilla, Carlos Torres-Cubilla, Ana Belen Nieto Librero and Purificacion Galindo Villardon
Galindo, M. P. (1986). Una alternativa de representacion simultanea: HJ-Biplot. Questiio, 10(1), 13-23.
Hoerl, A. E., & Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1), 55-67.
Zou, H., Hastie, T., & Tibshirani, R. (2006). Sparse principal component analysis. Journal of computational and graphical statistics, 15(2), 265-286.
1 | Ridge_HJBiplot(mtcars, Lambda = 0.2)
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