NADA2 (version 1.1.8)

ROSci: 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)

Value

Prints a lower (LCL) and upper (UCL) confidence interval based on the conf provided (Default is 95%)

Arguments

cenros.out

an ROS model output object (see details)

conf

Confidence coefficient of the interval (Default is 0.95)

printstat

Logical TRUE/FALSE option of whether to print the resulting statistics in the console window, or not. Default is TRUE.

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.

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. tools:::Rd_expr_doi("https://doi.org/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. tools:::Rd_expr_doi("https://doi.org/10.1002/(SICI)1097-0258(19970415)16:7<783::aid-sim488>3.0.CO;2-2")

See Also

NADA::ros

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)