ppc.predict {ppc} | R Documentation |
Function to do test set prediction for the PPC method
Description
This function does test set prediction for PPC method.
It predicts outcome classes for a list of peaks from test set spectra.
Usage
ppc.predict(centroid.fit, split.fit, logmz, peaklist.te, n.threshold = 30, threshold = NULL, metric = c("binomial", "euclidean", "absolute"), summ = c("mean", "median"))
Arguments
centroid.fit |
Result of a call to ppc.make.centroid.list |
split.fit |
Result of a call to ppc.find.splits |
logmz |
log of m/z values from training data |
peaklist.te |
List of peaks from test set- each component is a matrix of
log m/z values and peak intensities |
n.threshold |
Number of shrinkage thresholds to use |
threshold |
Threshold values to use |
metric |
"binomial","euclidean", or "absolute" |
summ |
"mean" or median" |
Value
yhat |
Matrix of predicted classes |
threshold |
Threshold values used. |
numsites |
Number of sites surviving the threshold for each shrinkage value |
sites |
List of sites surviving the threshold for each shrinkage value |
ind |
Indicator matrix of event ( peak intensity at site > cutpoint |
ind0 |
Indicator matrix of event ( peak intensity at site > cutpoint |
prob |
Matrix of estimated class probabilities |
ht |
Matrix of peak intensities |
Author(s)
Balasubramanian Narasimhan and Rob Tibshirani
Examples
## for a complete worked example of this function in a PPC analysis see
## http://www-stat.stanford.edu/~tibs/PPC/Rdist/Rscript.rawdata
[Package
ppc version 1.01
Index]