Animals2(robustbase)
Animals2()所属R语言包:robustbase
Brain and Body Weights for 65 Species of Land Animals
大脑和身体重量的65种陆地动物
译者:生物统计家园网 机器人LoveR
描述----------Description----------
A data frame with average brain and body weights for 62 species of land mammals and three others.
一个数据框的平均大脑和身体重量的62种陆地哺乳动物和其他三人。
Note that this is simply the union of Animals and mammals.
请注意,这仅仅是工会的Animals和mammals。
用法----------Usage----------
Animals2
格式----------Format----------
body body weight in kg
body体重(公斤)
brain brain weight in g
brain脑重g
注意----------Note----------
After loading the MASS package, the data set is simply constructed by Animals2 <- local({D <- rbind(Animals, mammals); unique(D[order(D$body,D$brain),])}).
加载MASS包后,将数据集构造简单Animals2 <- local({D <- rbind(Animals, mammals); unique(D[order(D$body,D$brain),])})。
Rousseeuw and Leroy (1987)'s "brain" data is the same as MASS's Animals (with Rat and Brachiosaurus interchanged, see the example below).
Rousseeuw和Leroy(1987年)的“大脑”的数据是一样的,MASS的Animals(鼠和腕互换中,见下面的例子)。
源----------Source----------
Weisberg, S. (1985) Applied Linear Regression. 2nd edition. Wiley, pp. 144–5.
韦斯伯格,S.(1985)应用线性回归。第2版。 Wiley出版社,第144-5页。
P. J. Rousseeuw and A. M. Leroy (1987) Robust Regression and Outlier Detection. Wiley, p. 57.
PJ Rousseeuw AM乐华(1987)稳健回归和异常检测。 Wiley出版社,页。 57。
参考文献----------References----------
Modern Applied Statistics with S. Forth Edition. Springer.
实例----------Examples----------
data(Animals2)
## Sensible Plot needs doubly logarithmic scale[的#明智的图需要双对数刻度]
plot(Animals2, log = "xy")
## Regression example plot:[#回归的例子图:]
plotbb <- function(bbdat) {
d.name <- deparse(substitute(bbdat))
plot(log(brain) ~ log(body), data = bbdat, main = d.name)
abline( lm(log(brain) ~ log(body), data = bbdat))
abline(MASS::rlm(log(brain) ~ log(body), data = bbdat), col = 2)
legend("bottomright", leg = c("lm", "rlm"), col=1:2, lwd=1, inset = 1/20)
}
plotbb(bbdat = Animals2)
## The `same' plot for Rousseeuw's subset:[#相同的图Rousseeuw的子集:]
data(Animals, package = "MASS")
brain <- Animals[c(1:24, 26:25, 27:28),]
plotbb(bbdat = brain)
lbrain <- log(brain)
plot(mahalanobis(lbrain, colMeans(lbrain), var(lbrain)),
main = "Classical Mahalanobis Distances")
mcd <- covMcd(lbrain)
plot(mahalanobis(lbrain,mcd$center,mcd$cov),
main = "Robust (MCD) Mahalanobis Distances")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
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