normConstCVCI {testassay} | R Documentation |
Log-centered confidence intervals from a Normal constant coeffficient of variation model
Description
Assume Y is normal with mean mu>0 and coefficient of variation theta, then Y/mu ~ N(1, theta^2). Get log-centered confidence intervals (when possible), meaning intervals such that log(y) +/- r(theta), where r(theta) is a constant function of theta.
Usage
normConstCVCI(y, theta, conf.level = 0.6827, eps = .Machine$double.eps^0.25)
Arguments
y |
vector of observed values, should be positive |
theta |
coefficient of variation (assumed known) |
conf.level |
Confidence level |
eps |
a small number used in the algorithm (look at code before changing) |
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.
normConstCVCI(3.4,.6)
# symmetric on log scale
log(normConstCVCI(3.4,.6))
[Package testassay version 0.1.1 Index]