Direct Orthogonal Signal Correction — direct

This function implements the Direct Orthogonal Signal Correction (DOSC) algorithm, as proposed by Westerhuis et al. (2001), to remove systematic variation from predictor variables, \(\textbf{X}\), that is orthogonal to the response variable(s), \(\textbf{Y}\).

Usage

direct_osc(
  x,
  y,
  ncomp = 10,
  center = TRUE,
  scale = FALSE,
  tol = 0.001,
  max_iter = 10
)

Arguments

x: A matrix or data frame of the predictor variables
y: A vector, matrix or data frame of the response variable(s)
ncomp: An integer specifying the number of principal components to retain for orthogonal processing. Default is 10.
center: A logical value specifying whether to center the data. Default is TRUE.
scale: A logical value specifying whether to scale the data. Default is FALSE.
tol: A numeric value representing the tolerance for convergence. The default value is 1e-3.
max_iter: An integer representing the maximum number of iterations. The default value is 10.

Value

A list with the following components:

correction: The corrected matrix.
loading: The loadings matrix.
score: The scores matrix.

Details

Different from the Orthogonal Signal Correction (OSC) algorithm, Wold et al. (1998), the DOSC algorithm firstly orthogonalizes the matrices \(\textbf{X}\) and \(\textbf{Y}\). Then principal components analysis (PCA) is performed on the orthogonalized \(\textbf{X}\) to obtain the scores \(\textbf{T}\) and loadings \(\textbf{P}\) matrices.

References

Westerhuis, J.A., Jong, S.D., Smilde, A.K., (2001). Direct orthogonal signal correction. Chemometrics Intell. Lab. Syst., 56(1):13-25
Wold, S., Antti, H., Lindgren, F., Ohman, J. (1998). Orthogonal signal correction of near-infrared spectra. Chemometrics Intell. Lab. Syst., 44(1):175-185.

Author

Christian L. Goueguel