Tikuv(VGAM)
Tikuv()所属R语言包：VGAM
A Short-tailed Symmetric Distribution
一个短尾对称分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Density, cumulative distribution function, quantile function and random generation for the short-tailed symmetric distribution of Tiku and Vaughan (1999).
密度，累积分布函数，分位数函数和随机生成的的短尾对称的TIKU和沃恩（1999）的分布。
用法----------Usage----------
dtikuv(x, d, mean = 0, sigma = 1, log = FALSE)
ptikuv(q, d, mean = 0, sigma = 1)
qtikuv(p, d, mean = 0, sigma = 1, ...)
rtikuv(n, d, mean = 0, sigma = 1, Smallno = 1.0e-6)
参数----------Arguments----------
参数：x, q
vector of quantiles.
向量的位数。
参数：p
vector of probabilities.
向量的概率。
参数：n
number of observations. Must be a positive integer of length 1.
若干意见。必须是一个长度为1的正整数。
参数：d, mean, sigma
arguments for the parameters of the distribution. See tikuv for more details. For rtikuv, arguments mean and sigma must be of length 1.
参数的分布参数。见tikuv更多详情。对于rtikuv，参数mean和sigma必须是长度为1。
参数：Smallno
Numeric, a small value used by the rejection method for determining the lower and upper limits of the distribution. That is, ptikuv(L) < Smallno and ptikuv(U) > 1-Smallno where L and U are the lower and upper limits respectively.
数字，一个较小的值，所使用的抑制方法，用于确定的上限和下限的分布。也就是说，ptikuv(L) < Smallno和ptikuv(U) > 1-Smallno其中L和U的上限和下限分别。
参数：...
Arguments that can be passed into uniroot.
参数可以传入uniroot。
参数：log
Logical. If log = TRUE then the logarithm of the density is returned.
逻辑。如果log = TRUE然后返回的密度的对数。
Details
详细信息----------Details----------
See tikuv for more details.
见tikuv更多详情。
值----------Value----------
dtikuv gives the density, ptikuv gives the cumulative distribution function, qtikuv gives the quantile function, and rtikuv generates random deviates.
dtikuv给出了密度，ptikuv给人的累积分布函数，qtikuv给出了分位数的功能，和rtikuv随机产生的偏离。
（作者）----------Author(s)----------
T. W. Yee
参见----------See Also----------
tikuv.
tikuv。
实例----------Examples----------
## Not run: par(mfrow = c(2, 1))[＃不运行：PAR（mfrow = C（2,1））]
x = seq(-5, 5, len = 401)
plot(x, dnorm(x), type = "l", col = "black", ylab = "", las = 1,
main = "Black is standard normal, others are dtikuv(x, d)")
lines(x, dtikuv(x, d = -10), col = "orange")
lines(x, dtikuv(x, d = -1 ), col = "blue")
lines(x, dtikuv(x, d = 1 ), col = "green")
legend("topleft", col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("d =", c(-10, -1, 1)))
plot(x, pnorm(x), type = "l", col = "black", ylab = "", las = 1,
main = "Black is standard normal, others are ptikuv(x, d)")
lines(x, ptikuv(x, d = -10), col = "orange")
lines(x, ptikuv(x, d = -1 ), col = "blue")
lines(x, ptikuv(x, d = 1 ), col = "green")
legend("topleft", col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("d =", c(-10, -1, 1)))
probs = seq(0.1, 0.9, by = 0.1)
ptikuv(qtikuv(p = probs, d = 1), d = 1) - probs # Should be all 0[应该是0]
## 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。
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发表于 2012-10-1 15:54:41
