Appalachia {rrcov} | R Documentation |
Annual maximum streamflow in central Appalachia
Description
The data on annual maximum streamflow at 104 gaging stations in the central Appalachia region of the United States contains the sample L-moments ratios (L-CV, L-skewness and L-kurtosis) as used by Hosking and Wallis (1997) to illustrate regional freqency analysis (RFA).
Usage
data(Appalachia)
Format
A data frame with 104 observations on the following 3 variables:
L-CV
L-coefficient of variation
L-skewness
L-coefficient of skewness
L-kurtosis
L-coefficient of kurtosis
Details
The sample L-moment ratios (L-CV, L-skewness and L-kurtosis) of a site are regarded as a point in three dimensional space.
Source
Hosking, J. R. M. and J. R. Wallis (1997), Regional Frequency Analysis: An Approach Based on L-moments. Cambridge University Press, p.175–185
References
Neykov, N.M., Neytchev, P.N., Van Gelder, P.H.A.J.M. and Todorov V. (2007), Robust detection of discordant sites in regional frequency analysis, Water Resources Research, 43, W06417, doi:10.1029/2006WR005322
Examples
data(Appalachia)
# plot a matrix of scatterplots
pairs(Appalachia,
main="Appalachia data set",
pch=21,
bg=c("red", "green3", "blue"))
mcd<-CovMcd(Appalachia)
mcd
plot(mcd, which="dist", class=TRUE)
plot(mcd, which="dd", class=TRUE)
## identify the discordant sites using robust distances and compare
## to the classical ones
mcd <- CovMcd(Appalachia)
rd <- sqrt(getDistance(mcd))
ccov <- CovClassic(Appalachia)
cd <- sqrt(getDistance(ccov))
r.out <- which(rd > sqrt(qchisq(0.975,3)))
c.out <- which(cd > sqrt(qchisq(0.975,3)))
cat("Robust: ", length(r.out), " outliers: ", r.out,"\n")
cat("Classical: ", length(c.out), " outliers: ", c.out,"\n")