lognormConstCVCI {testassay} | R Documentation |
log-normal constant CV model
Description
This function gets confidence intervals on mu=E(Y) assuming Y is lognormal and the coefficient of variation is known.
Usage
lognormConstCVCI(y, theta, conf.level = 0.6827)
Arguments
y |
Observed value |
theta |
coefficient of variation (assumed known) |
conf.level |
Confidence level |
Details
Let Y be lognormal, so that log(Y) is normal with mean xi and variance eta. Then E(Y) =mu = exp(xi+eta/2) and Var(Y)=sigma^2 = mu^2 (exp(eta)-1), so that the coefficient of variation is sigma/mu = sqrt( exp(eta)-1). We want to get log-centered confidence intervals on mu, meaning intervals such that log(y) +/- r(theta), where r(theta) is a constant function of theta.
Value
A list with the following components
obs y
lower lower confidence limit on mu=E(Y)
upper upper confidence limit on mu=E(Y)
Examples
# defaults to 68.27 percent confidence level, same level as Normal plus or minus 1 std dev.
lognormConstCVCI(3.4,.6)
# compare to normal constant CV model result
normConstCVCI(3.4,.6)
[Package testassay version 0.1.1 Index]