gevUC(VGAM)
gevUC()所属R语言包：VGAM
The Generalized Extreme Value Distribution
广义极值分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Density, distribution function, quantile function and random generation for the generalized extreme value distribution (GEV) with location parameter location, scale parameter scale and shape parameter shape.
密度，分布函数，分位数的功能和位置参数location，规模参数scale和形状参数shape随机生成的广义极值分布（GEV）。
用法----------Usage----------
dgev(x, location = 0, scale = 1, shape = 0, log = FALSE, tolshape0 =
sqrt(.Machine$double.eps), oobounds.log = -Inf, giveWarning = FALSE)
pgev(q, location = 0, scale = 1, shape = 0)
qgev(p, location = 0, scale = 1, shape = 0)
rgev(n, location = 0, scale = 1, shape = 0)
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. If length(n) > 1 then the length is taken to be the number required.
若干意见。如果length(n) > 1的长度是所需的数量。
参数：location
the location parameter mu.
位置参数mu。
参数：scale
the (positive) scale parameter sigma. Must consist of positive values.
（正）尺度参数sigma。必须由正面的价值观。
参数：shape
the shape parameter xi.
形状参数xi。
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。
参数：tolshape0
Positive numeric. Threshold/tolerance value for resting whether xi is zero. If the absolute value of the estimate of xi is less than this value then it will be assumed zero and a Gumbel distribution will be used.
正数值。阈值/公差值截断是否xi是零。如果xi的估计的绝对值是小于该值，则其将被假定为零，将使用一个Gumbel分布。
参数：oobounds.log, giveWarning
Numeric and logical. The GEV distribution has support in the region satisfying 1+shape*(x-location)/scale > 0. Outside that region, the logarithm of the density is assigned oobounds.log, which equates to a zero density. It should not be assigned a positive number, and ideally is very negative. Since egev uses this function it is necessary to return a finite value outside this region so as to allow for half-stepping. Both arguments are in support of this. This argument and others match those of egev.
数字和逻辑。 GEV分布在该区域的支持，满足1+shape*(x-location)/scale > 0。以外的区域的对数的密度分配oobounds.log，它等同于一个零密度。它不应该被分配一个正数，理想情况下是非常不利的。自从egev使用此功能，有必要在这个区域之外，以便返回一个有限的值，以允许半步。两个参数都是支持。这个论点和其他的egev。
Details
详细信息----------Details----------
See gev, the VGAM family function for estimating the two parameters by maximum likelihood estimation, for formulae and other details. Apart from n, all the above arguments may be vectors and are recyled to the appropriate length if necessary.
gev，的VGAM的家庭功能的估计两个参数的最大似然估计，公式和其他细节。除了n，所有上述参数可以是向量和被recyled到合适的长度，如果必要的。
值----------Value----------
dgev gives the density, pgev gives the distribution function, qgev gives the quantile function, and rgev generates random deviates.
dgev给出了密度，pgev给出了分布函数，qgev给出了分位数的功能，和rgev随机产生的偏离。
注意----------Note----------
The default value of xi = 0 means the default distribution is the Gumbel.
xi = 0的默认值是指默认的分布是Gumbel分布。
Currently, these functions have different argument names compared with those in the evd package.
目前，这些功能有不同的参数与那些在evd包的名称相比。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
An Introduction to Statistical Modeling of Extreme Values. London: Springer-Verlag.
参见----------See Also----------
gev, egev, vglm.control.
gev，egev，vglm.control。
实例----------Examples----------
## Not run: [＃不运行：]
x = seq(-3, 3, by = 0.01)
loc = 0; sigma = 1; xi = -0.4
plot(x, dgev(x, loc, sigma, xi), type = "l", col = "blue", ylim = c(0,1),
main = "Blue is density, red is cumulative distribution function",
sub = "Purple are 5,10,...,95 percentiles", ylab = "", las = 1)
abline(h = 0, col = "blue", lty = 2)
lines(qgev(seq(0.05, 0.95, by = 0.05), loc, sigma, xi),
dgev(qgev(seq(0.05, 0.95, by = 0.05), loc, sigma, xi), loc, sigma, xi),
col = "purple", lty = 3, type = "h")
lines(x, pgev(x, loc, sigma, xi), type = "l", col = "red")
abline(h = 0, lty = 2)
pgev(qgev(seq(0.05, 0.95, by = 0.05), loc, sigma, xi), loc, sigma, xi)
## 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。
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发表于 2012-10-1 15:36:55
