Appalachia(rrcov)
Appalachia()所属R语言包:rrcov
Annual maximum streamflow in central Appalachia
在阿巴拉契亚中部最大年径流量
译者:生物统计家园网 机器人LoveR
描述----------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).
年最大径流中央阿巴拉契亚美国区域在104量具站上的数据中包含的样品L-矩的比值(L-CV,L-偏度和L-峰度)所用的由霍斯和Wallis(1997)来说明区域块频率分析(RFA)。
用法----------Usage----------
data(Appalachia)
格式----------Format----------
A data frame with 104 observations on the following 3 variables:
一个数据框,104以下3个变量的观察:
L-CV L-coefficient of variation
L-CVL-变异系数
L-skewness L-coefficient of skewness
L-skewnessL-偏态系数
L-kurtosis L-coefficient of kurtosis
L-kurtosisL-峰度系数
Details
详细信息----------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.
样本L-矩比率(L-CV,L-偏度和L-峰度)的网页被视为作为三维空间中的一个点。
源----------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
霍斯金,JRM和JR瓦利斯(1997),区域频率分析:一种基于L-时刻。剑桥大学出版社,第175页-185
参考文献----------References----------
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
实例----------Examples----------
data(Appalachia)
# plot a matrix of scatterplots[绘制散点图矩阵]
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 [#找出不和谐的站点使用强劲的距离和比较]
## to the classical ones[#经典的]
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")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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