Nakagami(VGAM)
Nakagami()所属R语言包：VGAM
Nakagami Distribution
Nakagami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 Nakagami distribution.
密度，累积分布函数，Nakagami分布的分位数函数随机生成。
用法----------Usage----------
dnaka(x, shape, scale = 1, log = FALSE)
pnaka(q, shape, scale = 1)
qnaka(p, shape, scale = 1, ...)
rnaka(n, shape, scale = 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：shape, scale
arguments for the parameters of the distribution. See nakagami for more details. For rnaka, arguments shape and scale must be of length 1.
参数的分布参数。见nakagami更多详情。对于rnaka，参数shape和scale必须是长度为1。
参数：Smallno
Numeric, a small value used by the rejection method for determining the upper limit of the distribution. That is, pnaka(U) > 1-Smallno where U is the upper limit.
数字，一个较小的值，所使用的抑制方法，用于确定的分布的上限。也就是说pnaka(U) > 1-Smallno其中U是上限。
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 nakagami for more details.
见nakagami更多详情。
值----------Value----------
dnaka gives the density, pnaka gives the cumulative distribution function, qnaka gives the quantile function, and rnaka generates random deviates.
dnaka给出了密度，pnaka给人的累积分布函数，qnaka给出了分位数的功能，和rnaka随机产生的偏离。
（作者）----------Author(s)----------
T. W. Yee
参见----------See Also----------
nakagami.
nakagami。
实例----------Examples----------
## Not run: x = seq(0, 3.2, len = 200)[＃不运行：X = SEQ（0，3.2，长度= 200）]
plot(x, dgamma(x, shape = 1), type = "n", col = "black", ylab = "",
ylim = c(0,1.5), main = "dnaka(x, shape)")
lines(x, dnaka(x, shape = 1), col = "orange")
lines(x, dnaka(x, shape = 2), col = "blue")
lines(x, dnaka(x, shape = 3), col = "green")
legend(2, 1.0, col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("shape =", c(1, 2, 3)))
plot(x, pnorm(x), type = "n", col = "black", ylab = "",
ylim = 0:1, main = "pnaka(x, shape)")
lines(x, pnaka(x, shape = 1), col = "orange")
lines(x, pnaka(x, shape = 2), col = "blue")
lines(x, pnaka(x, shape = 3), col = "green")
legend(2, 0.6, col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("shape =", c(1, 2, 3)))
## End(Not run)[＃（不执行）]
probs = seq(0.1, 0.9, by = 0.1)
pnaka(qnaka(p = probs, shape = 2), shape = 2) - probs # Should be all 0[应该是0]
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。
|
发表于 2012-10-1 15:45:19
