Wdensities.mix: Compute smoothed densities for a spike-slab mixture...
In pmckeigue/wevid: Weight of evidence for quantifying performance of a binary classifier
Description
Compute smoothed densities for a spike-slab mixture distribution
Usage
1
Wdensities.mix(y, W, in.spike, range.xseq = c(-25, 25), x.stepsize = 0.01)
Arguments
y
Binary outcome label (0 for controls, 1 for cases).
W
Weight of evidence.
in.spike
logical vector same length as y, TRUE if in spike component,
FALSE otherwise. Typically used where high proportion of values of the predictor are zero
range.xseq
Range of points where the curves should be sampled.
x.stepsize
Distance between each point.
pmckeigue/wevid documentation built on May 29, 2019, 5:41 a.m.
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Description
Compute smoothed densities for a spike-slab mixture distribution
Usage
1 | Wdensities.mix(y, W, in.spike, range.xseq = c(-25, 25), x.stepsize = 0.01)
|
Arguments
y |
Binary outcome label (0 for controls, 1 for cases). |
W |
Weight of evidence. |
in.spike |
logical vector same length as y, TRUE if in spike component, FALSE otherwise. Typically used where high proportion of values of the predictor are zero |
range.xseq |
Range of points where the curves should be sampled. |
x.stepsize |
Distance between each point. |
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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