projected_osc: Projected Orthogonal Signal Correction

In ChristianGoueguel/specProc: Preprocessing Tools For Laser-Induced Breakdown Spectroscopy (LIBS) Spectra

Projected Orthogonal Signal Correction

Description

The projected orthogonal signal correction (POSC) method is a preprocessing technique used to remove systematic variation from predictor variables that is orthogonal to the response variable. This function implements the POSC algorithm for model fitting and prediction.

Usage

projected_osc(
  x,
  y,
  ncomp = 5,
  center = TRUE,
  scale = FALSE,
  tol = 1e-10,
  newdata = NULL
)

Arguments

x	A matrix or data frame of the predictor variables.
y	A vector of the response variable.
ncomp	An integer specifying the number of components to include in the POSC model. Default is 5.
center	A logical value indicating whether to mean-center x and y. Default is TRUE.
scale	A logical value indicating whether to scale x and y. Default is FALSE.
tol	A numeric value representing the tolerance for convergence. The default value is 1e-10.
newdata	A matrix or data frame of new predictor variables to be corrected using the POSC model.

Value

If newdata is provided, a list containing the following components:

• correction: The corrected matrix for the new data after applying POSC.

• scores: The orthogonal scores matrix for the new data. If newdata is not provided, a list containing the following components:

• model: A list containing the POSC model components:

  • loadings: The orthogonal loadings matrix.

  • weights: The orthogonal weights matrix.

Author(s)

Christian L. Goueguel

ChristianGoueguel/specProc documentation built on Nov. 9, 2024, 3:23 p.m.