Expectiles-Koenker(VGAM)
Expectiles-Koenker()所属R语言包：VGAM
Expectiles/Quantiles of the Koenker Distribution
Expectiles / Koenker分布的分位数的
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Density function, distribution function, and quantile/expectile function and random generation for the Koenker distribution.
密度函数，分布函数，和分量/ expectile的功能和随机生成的Koenker分布。
用法----------Usage----------
dkoenker(x, location = 0, scale = 1, log = FALSE)
pkoenker(q, location = 0, scale = 1, log = FALSE)
qkoenker(p, location = 0, scale = 1)
rkoenker(n, location = 0, scale = 1)
参数----------Arguments----------
参数：x, q
Vector of expectiles/quantiles. See the terminology note below.
向量的expectiles /位数。请参阅下面的术语说明。
参数：p
Vector of probabilities. These should lie in (0,1).
向量的可能性。这些在于(0,1)。
参数：n, log
See runif.
见runif。
参数：location, scale
Location and scale parameters. The latter should have positive values. Values of these vectors are recyled.
位置和尺度参数。后者应该有正面的价值观。这些向量的值recyled。
Details
详细信息----------Details----------
A Student-t distribution with 2 degrees of freedom and a scale parameter of sqrt(2) is equivalent to the standard Koenker distribution. Further details about this distribution are given in koenker.
以学生为t分布的自由和尺度参数sqrt(2)的2度是等同的标准Koenker分布。这种分布的进一步的细节给出了koenker。
值----------Value----------
dkoenker(x) gives the density function. pkoenker(q) gives the distribution function. qkoenker(p) gives the expectile and quantile function. rkoenker(n) gives n random variates.
dkoenker(x)给出的密度函数。 pkoenker(q)给出的分布函数。 qkoenker(p)给出了expectile和分位数的功能。 rkoenker(n)给n随机变数。
（作者）----------Author(s)----------
T. W. Yee
参见----------See Also----------
dt, koenker.
dt，koenker。
实例----------Examples----------
my_p = 0.25; y = rkoenker(nn <- 5000)
(myexp = qkoenker(my_p))
sum(myexp - y[y <= myexp]) / sum(abs(myexp - y)) # Should be my_p[应该是MY_P]
# Equivalently:[等价的：]
I1 = mean(y <= myexp) * mean( myexp - y[y <= myexp])
I2 = mean(y > myexp) * mean(-myexp + y[y > myexp])
I1 / (I1 + I2) # Should be my_p[应该是MY_P]
# Or:[或者：]
I1 = sum( myexp - y[y <= myexp])
I2 = sum(-myexp + y[y > myexp])
# Non-standard Koenker distribution[非标Koenker分布]
myloc = 1; myscale = 2
yy = rkoenker(nn, myloc, myscale)
(myexp = qkoenker(my_p, myloc, myscale))
sum(myexp - yy[yy <= myexp]) / sum(abs(myexp - yy)) # Should be my_p[应该是MY_P]
pkoenker(mean(yy), myloc, myscale) # Should be 0.5[应为0.5]
abs(qkoenker(0.5, myloc, myscale) - mean(yy)) # Should be 0[应为0]
abs(pkoenker(myexp, myloc, myscale) - my_p) # Should be 0[应为0]
integrate(f = dkoenker, lower = -Inf, upper = Inf,
locat = myloc, scale = myscale) # Should be 1[应该是1]
y <- seq(-7, 7, len = 201)
max(abs(dkoenker(y) - dt(y / sqrt(2), df = 2) / sqrt(2))) # Should be 0[应为0]
## Not run: plot(y, dkoenker(y), type = "l", col = "blue", las = 1,[＃不运行：图（Y，dkoenker（Y），类型为“L”，列=“蓝”，LAS = 1，]
ylim = c(0, 0.4), main = "Blue = Koenker; orange = N(0, 1)")
lines(y, dnorm(y), type = "l", col = "orange")
abline(h = 0, v = 0, lty = 2)
## End(Not run)[＃（不执行）]
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:32:53
