Generates a score contribution plot
Generates a the Score Contribution Graph both
an object of class
the first observaion(s) in the score(s) comparison.
the second observaion(s) in the score(s) comparison.
ScoreContrib is used to generates the score contributions for both PLS and PCA models. Up to two groups of score(s) can be selected. If only one group is selected, the contribution is measured to the model average. For PLS models the PCA loadings are replaced with the PLS weights.
The output of
ScoreContrib is a matrix of score contributions for the specified observation(s).
Nelson Lee Afanador (firstname.lastname@example.org)
MacGregor, Process Monitoring and Diagnosis by Multiblock PLS Methods, May 1994 Vol. 40, No. 5 AIChE Journal.
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data(Penta) ## Number of bootstraps set to 500 to demonstrate flexibility ## Use a minimum of 1000 (default) for results that support bootstraping mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1], ncomp = 2, validation = "oob", boots = 500) Score.Contributions1 <- ScoreContrib(mod1, obs1 = 1, obs2 = 3) plot(Score.Contributions1) Score.Contributions2 <- ScoreContrib(mod1, obs1 = c(1, 3), obs2 = c(5:10)) plot(Score.Contributions2) #PCA Model pc1 <- pcaFit(Penta[, -1]) Score.Contributions1 <- ScoreContrib(pc1, obs1 = 1, obs2 = 3) plot(Score.Contributions1)
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