rlplot.egev(VGAM)
rlplot.egev()所属R语言包：VGAM
Return Level Plot for GEV Fits
返回平积GEV适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A return level plot is constructed for a GEV-type model.
返回平积构造的GEV型模型。
用法----------Usage----------
rlplot.egev(object, plot.it = TRUE,
probability = c((1:9)/100, (1:9)/10, 0.95, 0.99, 0.995, 0.999),
add.arg = FALSE, xlab = "Return Period", ylab = "Return Level",
main = "Return Level Plot",
pch = par()$pch, pcol.arg = par()$col, pcex = par()$cex,
llty.arg = par()$lty, lcol.arg = par()$col, llwd.arg = par()$lwd,
slty.arg = par()$lty, scol.arg = par()$col, slwd.arg = par()$lwd,
ylim = NULL, log = TRUE, CI = TRUE, epsilon = 1e-05, ...)
参数----------Arguments----------
参数：object
A VGAM extremes model of the GEV-type, produced by vglm with a family function either "gev" or "egev".
AVGAM极端模型的GEV型，所产生的vglm是"gev"或"egev"家庭功能。
参数：plot.it
Logical. Plot it? If FALSE no plot will be done.
逻辑。图呢？ FALSE如果没有图将得到伸张。
参数：probability
Numeric vector of probabilities used.
数字矢量使用的概率。
参数：add.arg
Logical. Add the plot to an existing plot?
逻辑。添加图现有的图？
参数：xlab
Caption for the x-axis. See par.
首领的x轴。见par。
参数：ylab
Caption for the y-axis. See par.
首领为y轴。见par。
参数：main
Title of the plot. See title.
标题的图。见title。
参数：pch
Plotting character. See par.
绘制字符。见par。
参数：pcol.arg
Color of the points. See the col argument of par.
的各点的颜色。请参阅colpar参数。
参数：pcex
Character expansion of the points. See the cex argument of par.
字符扩展之分。请参阅cexpar参数。
参数：llty.arg
Line type. Line type. See the lty argument of par.
线路类型。线路类型。请参阅ltypar参数。
参数：lcol.arg
Color of the lines. See the col argument of par.
线条的颜色。请参阅colpar参数。
参数：llwd.arg
Line width. See the lwd argument of par.
线条宽度。请参阅lwdpar参数。
参数：slty.arg, scol.arg, slwd.arg
Correponding arguments for the lines used for the confidence intervals. Used only if CI=TRUE.
Correponding参数的置信区间的线条。用只有CI=TRUE。
参数：ylim
Limits for the y-axis. Numeric of length 2.
的y轴的限制。数字的长度为2。
参数：log
Logical. If TRUE then log="" otherwise log="x". This changes the labelling of the x-axis only.
逻辑。如果TRUE然后log=""，否则log="x"。本仅改变标签的x轴。
参数：CI
Logical. Add in a 95 percent confidence interval?
逻辑。添加95％的置信区间？
参数：epsilon
Numeric, close to zero. Used for the finite-difference approximation to the first derivatives with respect to each parameter. If too small, numerical problems will occur.
数字，靠近为零。用于相对于每个参数的一阶导数的有限差分近似。如果过小，数值就会出现问题。
参数：...
Arguments passed into the plot function when setting up the entire plot. Useful arguments here include sub and las.
到plot函数传递参数时，设立了整个图。有用的参数包括：sub和las。
Details
详细信息----------Details----------
A return level plot plots zp versus log(yp). It is linear if the shape parameter xi=0. If xi<0 then the plot is convex with asymptotic limit as p approaches zero at mu-sigma/xi. And if xi>0 then the plot is concave and has no finite bound. Here, G(zp) = 1-p where 0<p<1 (p corresponds to the argument probability) and G is the cumulative distribution function of the GEV distribution. The quantity zp is known as the return level associated with the return period 1/p. For many applications, this means zp is exceeded by the annual maximum in any particular year with probability p.
返回平积曲线zp与log(yp)。它是线性的，如果形状参数xi=0。如果xi<0然后图是凸的渐近极限p在mu-sigma/xi趋近于零。如果xi>0的图是凹的，并没有有限约束。在这里，G(zp) = 1-p其中0<p<1（p对应的说法probability）和G是GEV分布的累积分布函数。的数量zp的返回电平被称为与回收期1/p相关。对于许多应用程序，这意味着zp超过年度最高在任何特定年份的概率p。
The points in the plot are the actual data.
在图中的点是实际的数据。
值----------Value----------
In the post slot of the object is a list called rlplot with list components
在post插槽的对象是被称为rlplot的列表组件的列表
参数：yp
-log(probability), which is used on the x-axis.
-log(probability)，它是用来在x-轴。
参数：zp
values which are used for the y-axis
用于y轴的值
参数：lower, upper
lower and upper confidence limits for the 95 percent confidence intervals evaluated at the values of probability (if CI=TRUE).
上限和下限的置信区间为95％的置信区间，评估值probability（如果CI=TRUE“）。
注意----------Note----------
The confidence intervals are approximate, being based on finite-difference approximations to derivatives.
的置信区间是近似的，是基于有限差分近似的衍生工具。
（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----------
egev.
egev。
实例----------Examples----------
gdata = data.frame(y = rgev(n <- 100, scale = 2, shape = -0.1))
fit = vglm(y ~ 1, egev, gdata, trace = TRUE)
# Identity link for all parameters:[所有参数的标识链接：]
fit2 = vglm(y ~ 1, egev(lshape = identity, lscale = identity,
iscale = 10), gdata, trace = TRUE)
coef(fit2, matrix = TRUE)
## Not run: [＃不运行：]
par(mfrow = c(1, 2))
rlplot(fit) -> i1
rlplot(fit2, pcol = "darkorange", lcol = "blue", log = FALSE,
scol = "darkgreen", slty = "dashed", las = 1) -> i2
range(i2@post$rlplot$upper - i1@post$rlplot$upper) # Should be near 0[应该是接近0]
range(i2@post$rlplot$lower - i1@post$rlplot$lower) # Should be near 0[应该是接近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 15:51:53
