Description Usage Format Details Source References Examples

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).

1 |

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

The sample L-moment ratios (L-CV, L-skewness and L-kurtosis) of a site are regarded as a point in three dimensional space.

Hosking, J. R. M. and J. R. Wallis (1997), *Regional Frequency Analysis: An
Approach Based on L-moments.* Cambridge University Press, p.175–185

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,
http://www.agu.org/pubs/crossref/2007/2006WR005322.shtml

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
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")
``` |

rrcov documentation built on May 20, 2017, 1:07 a.m.

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