StatisticSettings_MakeModel_pca_mdatools — StatisticSettings_MakeModel_pca

Makes a Principle Component Analysis (PCA) model based on the R package mdatools.

Usage

StatisticSettings_MakeModel_pca_mdatools(
  center = FALSE,
  scale = FALSE,
  ncomp = NULL,
  exclrows = NULL,
  exclcols = NULL,
  x.test = NULL,
  method = "svd",
  rand = NULL,
  lim.type = "ddmoments",
  alpha = 0.05,
  gamma = 0.01,
  info = ""
)

Arguments

center: Logical (length 1) indicating if the data should be centered.
scale: Logical (length 1) indicating if the data should be scaled.
ncomp: Integer (length 1) with the number of components to be calculated.
exclrows: Integer vector with the row indices to be excluded.
exclcols: Integer vector with the column indices to be excluded.
x.test: A data.frame with the test data.
method: Character (length 1) with the method to be used for PCA. Possible values are "svd" and "nipals".
rand: Integer (length 1) with the random seed.
lim.type: Character (length 1) with the type of limit for the PCA. Possible values are "jm" Jackson-Mudholkar approach, "chisq" based on chi-square distribution, "ddmoments" and "ddrobust" related to data driven method. It is highly recommended to concult the original documentation in pca for more information.
alpha: Numeric (length 1) with the alpha value for the PCA.
gamma: Numeric (length 1) with the gamma value for the PCA.
info: Character (length 1) with additional information.

Value

A StatisticSettings_MakeModel_pca_mdatools object.

References

Kucheryavskiy S (2020). “mdatools – R package for chemometrics.” Chemometrics and Intelligent Laboratory Systems, 198, 103937. ISSN 0169-7439, doi:10.1016/j.chemolab.2020.103937 , https://www.sciencedirect.com/science/article/pii/S0169743919305672.