Computes confidence intervals on regression on order statistics (ROS) mean
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.
ROSci(cenros.out, conf = 0.95, printstat = TRUE)
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.Prints a lower (LCL) and upper (UCL) confidence interval based on the conf provided (Default is 95%)
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.
data(Brumbaugh) myros <- NADA::ros(Brumbaugh$Hg,Brumbaugh$HgCen) summary(myros) # ROS Mean mean(myros$modeled) # 95% CI around the ROS mean ROSci(myros)
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")
NADA::ros