Wdensities.unadjusted: Calculate the unadjusted smoothed densities of W in cases and...
In pmckeigue/wevid: Weight of evidence for quantifying performance of a binary classifier
Description
Usage
Arguments
Value
Description
Calculate the unadjusted smoothed densities of W in cases and in controls
Usage
1
2
Wdensities.unadjusted(y, W, range.xseq = c(-25, 25), x.stepsize = 0.01,
adjust.bw = 1)
Arguments
y
Binary outcome label (0 for controls, 1 for cases).
W
Weight of evidence.
range.xseq
Range of points where the curves should be sampled.
x.stepsize
Distance between each point.
adjust.bw
Bandwidth adjustment.
Value
unadjusted density object
pmckeigue/wevid documentation built on May 29, 2019, 5:41 a.m.
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Description Usage Arguments Value
Description
Calculate the unadjusted smoothed densities of W in cases and in controls
Usage
1 2 | Wdensities.unadjusted(y, W, range.xseq = c(-25, 25), x.stepsize = 0.01,
adjust.bw = 1)
|
Arguments
y |
Binary outcome label (0 for controls, 1 for cases). |
W |
Weight of evidence. |
range.xseq |
Range of points where the curves should be sampled. |
x.stepsize |
Distance between each point. |
adjust.bw |
Bandwidth adjustment. |
Value
unadjusted density object
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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