lognormConstCVCI: log-normal constant CV model

In sachsmc/testassay: A Hypothesis Testing Framework for Validating an Assay for Precision

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)

sachsmc/testassay documentation built on June 15, 2020, 12:33 p.m.