Compute the negative logarithm of the Expected Improvement of a
set of candidate solutions.
Based on mean and standard deviation of a candidate solution,
this estimates the expectation of improvement. Improvement
considers the amount by which the best known value (best observed value)
is exceeded by the candidates.
Usage
expectedImprovement(mean, sd, min)
Arguments
mean
vector of predicted means of the candidate solutions.
sd
vector of estimated uncertainties / standard deviations of the candidate solutions.
min
minimal observed value.
Value
a vector with the negative logarithm of the expected improvement values, -log10(EI).
# NOT RUN {mean <- 1:10#mean of the candidatessd <- 10:1#st. deviation of the candidatesmin <- 5 #best known valueEI <- expectedImprovement(mean,sd,min)
EI
# }