resampleScoreModelPair | R Documentation |
Studentized bootstrap test of strength of scoreFn(yValues,model1Values) > scoreFn(yValues,model1Values) sampled with replacement.
resampleScoreModelPair(
model1Values,
model2Values,
yValues,
scoreFn,
...,
na.rm = FALSE,
returnScores = FALSE,
nRep = 100,
parallelCluster = NULL,
sameSample = FALSE
)
model1Values |
numeric array of predictions (model to test). |
model2Values |
numeric array of predictions (reference model). |
yValues |
numeric/logical array of outcomes, dependent, or truth values |
scoreFn |
function with signature scoreFn(modelValues,yValues) returning scalar numeric score. |
... |
not used, forces later arguments to be bound by name. |
na.rm |
logical, if TRUE remove NA values |
returnScores |
logical if TRUE return detailed resampledScores. |
nRep |
integer number of repititions to perform. |
parallelCluster |
optional snow-style parallel cluster. |
sameSample |
logical if TRUE use the same sample in computing both scores during bootstrap replication (else use independent samples). |
True confidence intervals are harder to get right (see "An Introduction to the Bootstrap", Bradely Efron, and Robert J. Tibshirani, Chapman & Hall/CRC, 1993.), but we will settle for simple p-value estimates.
summaries
set.seed(25325)
y <- 1:5
m1 <- c(1,1,2,2,2)
m2 <- c(1,1,1,1,2)
cor(m1,y)
cor(m2,y)
f <- function(modelValues,yValues) {
if((sd(modelValues)<=0)||(sd(yValues)<=0)) {
return(0)
}
cor(modelValues,yValues)
}
resampleScoreModelPair(m1,m2,y,f)
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