SCOUTer (version 1.0.0)

distplotsimple: displotsimple

Description

Returns the distance plot directly providing the coordinates and Upper Control Limits.

Usage

distplotsimple(
  T2,
  SPE,
  lim.t2,
  lim.spe,
  ncomp,
  obstag = matrix(0, length(T2), 1),
  alpha = 0.05,
  plottitle = "Distance plot\n"
)

Arguments

T2

Vector with the Hotelling's T^2 values for each observation.

SPE

Vector with the SPE values for each observation.

lim.t2

Value of the Upper Control Limit for the T^2 statistic.

lim.spe

Value of the Upper Control Limit for the SPE.

ncomp

An integer indicating the number of PCs.

obstag

Optional column vector of integers indicating the group of each observation (0 or 1). Default value set to matrix(0, nrow(X), 1).

alpha

Optional number between 0 and 1 expressing the type I risk assumed in the computation of the Upper Control Limits (UCL) set to 0.05 (5 %) by default.

plottitle

Optional string with the plot title, "Distance plot" by default.

Value

distplotobj ggplot object with the generated distance plot.

Details

Coordinates are expressed in terms of the Hotelling's T^2 (T^2, x-axis) and the Squared Prediction Error (SPE, y-axis). Observations can be identified by the obstag input argument.

Examples

# NOT RUN {
X <- as.matrix(X)
pcamodel.ref <- pcamb_classic(X[1:40,], 2, 0.05, "cent") # PCA-MB with first 40 
# observations
pcaproj <- pcame(X[-c(1:40),], pcamodel.ref) # Project last observations
distplotsimple(pcaproj$T2, pcaproj$SPE, pcamodel.ref$limt2, pcamodel.ref$limspe,
pcamodel.ref$ncomp)

pcaproj <- pcame(X, pcamodel.ref) # Project all observations
tags <- dotag(X[1:40,], X[-c(1:40),]) # 0's for observations used in PCA-MB
distplotsimple(pcaproj$T2, pcaproj$SPE, pcamodel.ref$limt2, pcamodel.ref$limspe, 
pcamodel.ref$ncomp, obstag = tags)
# }