Description Usage Arguments Value Examples
Summary evaluation of predictive performance
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## S3 method for class 'Wdensities'
summary(object, ...)
## S3 method for class 'Wdensities'
mean(x, ...)
auroc.crude(densities)
auroc.model(densities)
lambda.crude(densities)
lambda.model(densities)
|
object, x, densities |
Densities object produced by
|
... |
Further arguments passed to or from other methods. These are currently ignored. |
summary
returns a data frame that reports the number of cases and
controls, the test log-likelihood, the crude and model-based C-statistic
and expected weight of evidence Lambda.
mean
returns a numeric vector listing the mean densities of the weight
of evidence in controls and in cases.
auroc.crude
and auroc.model
return the area under the ROC curve
according to the crude and the model-based densities of weight of evidence,
respectively.
lambda.crude
and lambda.model
return the expected weight of
evidence (expected information for discrimination) in bits from the crude
and the model-based densities, respectively.
1 2 3 4 5 6 7 | data(cleveland)
densities <- with(cleveland, Wdensities(y, posterior.p, prior.p))
summary(densities)
mean(densities)
auroc.model(densities)
lambda.model(densities)
|
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