Description Usage Arguments Details Value
Calculate the non-parametric critical value threshold estimates for the SPE and T2 monitoring test statistics.
1 |
pca_object |
A list with class "PCA_model" from the internal PCA_model() function |
alpha |
The upper 1 - alpha quantile of the SPE and T2 densities from the training data passed to this function. Defaults to 0.01. |
... |
Lazy dots for additional internal arguments |
This function takes in a pca object returned by the pca() function and a threshold level defaulting to alpha = 0.1 percent of the observations. This critical quantile is set this low to reduce false alarms, as described in Kazor et al (2016). The function then returns a calculated SPE threshold corresponding to the 1 - alpha critical value, a similar T2 threshold, and the projection and Lambda Inverse (1 / eigenvalues) matrices passed through from the pca() function call.
A list with classes "threshold" and "pca" containing:
SPE_threshold – the 1 - alpha quantile of the estimated SPE density
T2_threshold – the 1 - alpha quantile of the estimated Hotelling's T2 density
projectionMatrix – a projection matrix from the data feature space to the feature subspace which preserves some pre-specified proportion of the energy of the data scatter matrix.
LambdaInv – a diagonal matrix of the reciprocal eigenvalues of the data scatter matrix
T2 – the vector of Hotelling's T2 test statistic values for each of the n observations in "data"
SPE – the vector of SPE test statistic values for each of the n observations in "data"
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