XresidualContrib {mvdalab} | R Documentation |
Generates the squared prediction error contributions and contribution plot
Description
Generates the squared prediction error (SPE) contributions and graph both mvdareg
and mvdapca
objects.
Usage
XresidualContrib(object, ncomp = object$ncomp, obs1 = 1)
Arguments
object |
an object of class |
ncomp |
the number of components to include in the SPE calculation. |
obs1 |
the observaion in SPE assessment. |
Details
XresidualContrib
is used to generates the squared prediction error (SPE) contributions and graph for both PLS and PCA models. Only one observation at a time is supported.
Value
The output of XresidualContrib
is a matrix of score contributions for a specified observation and the corresponding graph.
Author(s)
Nelson Lee Afanador (nelson.afanador@mvdalab.com)
References
MacGregor, Process Monitoring and Diagnosis by Multiblock PLS Methods, May 1994 Vol. 40, No. 5 AIChE Journal
Examples
data(Penta)
mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1],
ncomp = 2, validation = "loo")
XresidualContrib(mod1, ncomp = 2, obs1 = 3)
## Not run:
#PCA Model
pc1 <- pcaFit(Penta[, -1], ncomp = 4)
XresidualContrib(pc1, ncomp = 3, obs1 = 3)
## End(Not run)
[Package mvdalab version 1.7 Index]