Expectiles-Normal(VGAM)
Expectiles-Normal()所属R语言包：VGAM
Expectiles of the Normal Distribution
Expectiles的正态分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Density function, distribution function, and expectile function and random generation for the distribution associated with the expectiles of a normal distribution.
密度函数，分布函数，expectile的功能和随机生成的分布与正常分布的expectiles。
用法----------Usage----------
denorm(x, mean = 0, sd = 1, log = FALSE)
penorm(q, mean = 0, sd = 1, log = FALSE)
qenorm(p, mean = 0, sd = 1, Maxit_nr = 10, Tol_nr = 1.0e-6)
renorm(n, mean = 0, sd = 1)
参数----------Arguments----------
参数：x, p, q
See deunif.
见deunif。
参数：n, mean, sd, log
See rnorm.
见rnorm。
参数：Maxit_nr, Tol_nr
See deunif.
见deunif。
Details
详细信息----------Details----------
General details are given in deunif including a note regarding the terminology used. Here, norm corresponds to the distribution of interest, F, and enorm corresponds to G. The addition of “e” is for the "other" distribution associated with the parent distribution. Thus denorm is for g, penorm is for G, qenorm is for the inverse of G, renorm generates random variates from g.
一般的详情载于deunif包括注意事项所使用的术语。在这里，norm相对应的利益分配，F和enorm对应于G。加上“e”是为“其他”的分布与父分布。因此denorm是g，penorm是G，qenorm是G的逆，renorm生成随机变元从g。
For qenorm the Newton-Raphson algorithm is used to solve for y satisfying p = G(y). Numerical problems may occur when values of p are very close to 0 or 1.
对于qenorm Newton-Raphson算法是用来解决y满意p = G(y)。数值时可能出现的问题p值非常接近0或1。
值----------Value----------
denorm(x) gives the density function g(x). penorm(q) gives the distribution function G(q). qenorm(p) gives the expectile function: the value y such that G(y)=p. renorm(n) gives n random variates from G.
denorm(x)给出了密度函数g(x)。 penorm(q)给出了分布函数G(q)。 qenorm(p)给出了expectile的功能：价值y等G(y)=p。 renorm(n)给从nG随机变数。
（作者）----------Author(s)----------
T. W. Yee
参见----------See Also----------
deunif, deexp, dnorm, amlnormal, lms.bcn.
deunif，deexp，dnorm，amlnormal，lms.bcn。
实例----------Examples----------
my_p = 0.25; y = rnorm(nn <- 1000)
(myexp = qenorm(my_p))
sum(myexp - y[y <= myexp]) / sum(abs(myexp - y)) # Should be my_p[应该是MY_P]
# Non-standard normal[非标正常]
mymean = 1; mysd = 2
yy = rnorm(nn, mymean, mysd)
(myexp = qenorm(my_p, mymean, mysd))
sum(myexp - yy[yy <= myexp]) / sum(abs(myexp - yy)) # Should be my_p[应该是MY_P]
penorm(-Inf, mymean, mysd) # Should be 0[应为0]
penorm( Inf, mymean, mysd) # Should be 1[应该是1]
penorm(mean(yy), mymean, mysd) # Should be 0.5[应为0.5]
abs(qenorm(0.5, mymean, mysd) - mean(yy)) # Should be 0[应为0]
abs(penorm(myexp, mymean, mysd) - my_p) # Should be 0[应为0]
integrate(f = denorm, lower=-Inf, upper = Inf,
mymean, mysd) # Should be 1[应该是1]
## Not run: [＃不运行：]
par(mfrow = c(2, 1))
yy = seq(-3, 3, len = nn)
plot(yy, denorm(yy), type = "l", col="blue", xlab = "y", ylab = "g(y)",
main = "g(y) for N(0,1); dotted green is f(y) = dnorm(y)")
lines(yy, dnorm(yy), col="darkgreen", lty="dotted", lwd=2) # 'original'[“原始的”]
plot(yy, penorm(yy), type = "l", col = "blue", ylim = 0:1,
xlab = "y", ylab = "G(y)", main = "G(y) for N(0,1)")
abline(v = 0, h = 0.5, col = "red", lty = "dashed")
lines(yy, pnorm(yy), col = "darkgreen", lty = "dotted", lwd = 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 15:32:58
