SCOUTer (version 1.0.0)

scoutgrid: scoutgrid

Description

Shift of an array following a grid pattern.

Usage

scoutgrid(
  X,
  pcaref,
  T2.target = NA,
  SPE.target = NA,
  nsteps.t2 = 1,
  nsteps.spe = 1,
  gspe = 1,
  gt2 = 1
)

Arguments

X

Matrix with observations that will be shifted as rows.

pcaref

List with the elements of a PCA model:

• m: mean.

• s: standard deviation.

• prepro: preprocessing: "none", "cent" or "autosc".

• P: loading matrix.

• lambda: vector with variances of each PC.

T2.target

A number indicating the target value for the T^2_A after the shift. Set to NA by default.

SPE.target

A number indicating the target value for the SPE after the shift. Set to NA by default.

nsteps.t2

An integer indicating the number of steps in which the shift from the reference to the target value of the T^2_A will be performed. Set to 1 by default.

nsteps.spe

An integer indicating the number of steps in which the shift from the reference to the target value of the SPE will be performed. Set to 1 by default.

gspe

A number indicating the term that will tune the spacing between steps for the SPE. Set to 1 by default (linear spacing).

gt2

A number indicating the term that will tune the spacing between steps for the SPE. Set to 1 by default (linear spacing).

Value

list with elements:

• X: matrix with the new and shifted data.

• SPE: SPE of each one of the generated outliers in the list element X.

• T2: T^2 of each one of the generated outliers in the list element X.

• step.spe: step of each observation according to the shift of the SPE.

• step.t2: step of each observation according to the shift of the T^2.

• tag: is a vector of ones as long as the number of generated observations.

Examples

# NOT RUN {
X <- as.matrix(X)
pcamodel.ref <- pcamb_classic(X, 3, 0.1, "autosc") # PCA-MB with all observations
# Shift a set of observations increasing the T^2  and the SPE in 3 and 2 linear and 
# non-linear steps respectively:
outgrid <- scoutgrid(X, pcamodel.ref, T2.target = matrix(40, nrow(X), 1), 
SPE.target = matrix(50, nrow(X), 1), nsteps.t2 = 3, nsteps.spe = 2, gspe = 4)
# }