penalBrier: Evaluation of the performance of risk prediction models with...

Description Usage Arguments Details Value References Examples

View source: R/add.r

Description

Evaluation of the performance of risk prediction models with binary status response variable.

Usage

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penalBrier(Data, coeffP)

Arguments

Data

a data matrix; in the first column there should be the response variable y. If you give the training dataset it will calculate the Brier score.

coeffP

a named vector of coefficients

Details

Brier score is a measure for classification performance of a binary classifier. Its values range between [0,1] and the closest is to 0 the better the classifier is. The area under the curve and the Brier score is used to summarize and compare the performance.

Value

the Brier score (misclassification error)

References

Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review 78.

Examples

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# use the penalBrier function on a simulated dataset, with given lamda and w.
set.seed(14)
beta    <- c(3, 2, -1.6, -4)
noise   <- 5
simData <- SimData(N=100,beta=beta, noise=noise, corr=FALSE)

before   <- Sys.time()
stepPenal<- StepPenal(Data=simData, lamda=1.2, w=0.4)
(totRun  <- Sys.time() - before)

(coeff<- stepPenal$coeffP)
 me <- penalBrier(simData,coeff)

stepPenal documentation built on May 29, 2017, 3:25 p.m.