ROSci {NADA2} | R Documentation |
Computes confidence intervals on regression on order statistics (ROS) mean
Description
Uses ROS model output from the NADA
package and computes the Zhou and Gao 1997 modified Cox’s method two-sided confidence interval around the mean for a lognormal distribution. Computes a t-interval for a gaussian ROS model output.
Usage
ROSci(cenros.out, conf = 0.95, printstat = TRUE)
Arguments
cenros.out |
an ROS model output object (see details) |
conf |
Confidence coefficient of the interval (Default is 0.95) |
printstat |
Logical |
Details
This function uses an ROS model output based on the ros
function in the NADA
package. The lognormal distribution is the default for the NADA package but a gaussian distribution is optional here.
For more detail on ROS modeling see the ros
help file (?NADA::ros
).
For implementation of ROSci(...)
see the examples below.
Value
Prints a lower (LCL) and upper (UCL) confidence interval based on the conf
provided (Default is 95%)
References
Helsel, D.R., 2011. Statistics for censored environmental data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.
Lee, L., Helsel, D., 2005. Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics. Computers & Geosciences 31, 1241–1248. doi: 10.1016/j.cageo.2005.03.012
Zhou, X.-H., Gao, S., 1997. Confidence Intervals for the Log-Normal Mean. Statistics in Medicine 16, 783–790. doi: 10.1002/(SICI)1097-0258(19970415)16:7<783::AID-SIM488>3.0.CO;2-2
See Also
Examples
data(Brumbaugh)
myros <- NADA::ros(Brumbaugh$Hg,Brumbaugh$HgCen)
summary(myros)
# ROS Mean
mean(myros$modeled)
# 95% CI around the ROS mean
ROSci(myros)