Cascades: Annual precipitation totals for the North Cascades region

In rrcov: Scalable Robust Estimators with High Breakdown Point

Annual precipitation totals for the North Cascades region

Description

The data on annual precipitation totals for the North Cascades region contains the sample L-moments ratios (L-CV, L-skewness and L-kurtosis) for 19 sites as used by Hosking and Wallis (1997), page 53, Table 3.4, to illustrate screening tools for regional freqency analysis (RFA).

Usage

data(Cascades)

Format

A data frame with 19 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. 52–53

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(Cascades)

    # plot a matrix of scatterplots
    pairs(Cascades,
          main="Cascades data set",
          pch=21,
          bg=c("red", "green3", "blue"))

    mcd<-CovMcd(Cascades)
    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
    rd <- sqrt(getDistance(mcd))
    ccov <- CovClassic(Cascades)
    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 July 9, 2023, 6:03 p.m.