plot.boot(boot)
plot.boot()所属R语言包：boot
Plots of the Output of a Bootstrap Simulation
图的Bootstrap仿真的输出
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This takes a bootstrap object and produces plots for the bootstrap replicates of the variable of interest.
这需要一个引导对象和生产，引导感兴趣的变量复制的图。
用法----------Usage----------
## S3 method for class 'boot'
plot(x, index = 1, t0 = NULL, t = NULL, jack = FALSE,
qdist = "norm", nclass = NULL, df, ...)
参数----------Arguments----------
参数：x
An object of class "boot" returned from one of the bootstrap generation functions.
一个类的对象"boot"返回引导新一代功能之一。
参数：index
The index of the variable of interest within the output of boot.out. This is ignored if t and t0 are supplied.
利益内boot.out输出变量的指数。如果t和t0提供这被忽略。
参数：t0
The original value of the statistic. This defaults to boot.out$t0[index] unless t is supplied when it defaults to NULL. In that case no vertical line is drawn on the histogram.
统计的原始值。这默认为boot.out$t0[index]除非t提供时，它默认为NULL。在这种情况下，没有垂直线的绘制直方图。
参数：t
The bootstrap replicates of the statistic. Usually this will take on its default value of boot.out$t[,index], however it may be useful sometimes to supply a different set of values which are a function of boot.out$t.
引导重复统计。通常将其默认值boot.out$t[,index]，但它可能是有用的，有时提供一套不同的价值观，这是一个boot.out$t功能。
参数：jack
A logical value indicating whether a jackknife-after-bootstrap plot is required. The default is not to produce such a plot.
一个逻辑值，指明是否折刀后，引导图需要。默认情况下是不会产生这样一个图。
参数：qdist
The distribution against which the Q-Q plot should be drawn. At present "norm" (normal distribution - the default) and "chisq" (chi-squared distribution) are the only possible values.
应制定对分配的QQ图。目前"norm"（正态分布 - 默认）和"chisq"（卡方分布）是唯一可能的值。
参数：nclass
An integer giving the number of classes to be used in the bootstrap histogram. The default is the integer between 10 and 100 closest to ceiling(length(t)/25).
一个整数，要引导直方图的班级数目。默认是最接近ceiling(length(t)/25)10和100之间的整数。
参数：df
If qdist is "chisq" then this is the degrees of freedom for the chi-squared distribution to be used. It is a required argument in that case.
如果qdist是"chisq"那么这就是要使用卡方分布的自由程度。在这种情况下它是一个必需的参数。
参数：...
When jack is TRUE additional parameters to jack.after.boot can be supplied. See the help file for jack.after.boot for details of the possible parameters.
当jack是TRUEjack.after.boot额外的参数可以提供。请参阅帮助文件jack.after.boot可能的参数的详细信息。
Details
详情----------Details----------
This function will generally produce two side-by-side plots. The left plot will be a histogram of the bootstrap replicates. Usually the breaks of the histogram will be chosen so that t0 is at a breakpoint and all intervals are of equal length. A vertical dotted line indicates the position of t0. This cannot be done if t is supplied but t0 is not and so, in that case, the breakpoints are computed by hist using the nclass argument and no vertical line is drawn.
此功能一般会产生两个边侧图。左边的图将是一个引导直方图复制。一般将选择直方图的截断，使t0是在一个断点，所有的时间间隔长度相等。一个垂直的虚线表示位置t0。这不能做t如果提供，但t0不等，在这种情况下，断点hist使用nclass论点，并没有垂直线是计算绘制。
The second plot is a Q-Q plot of the bootstrap replicates. The order statistics of the replicates can be plotted against normal or chi-squared quantiles. In either case the expected line is also plotted. For the normal, this will have intercept mean(t) and slope sqrt(var(t)) while for the chi-squared it has intercept 0 and slope 1.
第二个图是一个引导复制的QQ图。复制的订单统计数据，可以绘制对正常或卡方位数。在两种情况下，预计线也绘制。为正常，这将有拦截mean(t)和斜坡sqrt(var(t))而卡方拦截1 0和斜坡。
If jack is TRUE a third plot is produced beneath these two. That plot is the jackknife-after-bootstrap plot. This plot may only be requested when nonparametric simulation has been used. See jack.after.boot for further details of this plot.
如果jack是TRUE第三个图是下面这两个。这一图是折刀后，引导图。此图只可要求时，已被用于非参数模拟。看到jack.after.boot这个图的进一步细节。
值----------Value----------
boot.out is returned invisibly.
boot.out返回无形。
副作用----------Side Effects----------
All screens are closed and cleared and a number of plots are produced on the current graphics device. Screens are closed but not cleared at termination of this function.
关闭所有屏幕和清除当前图形设备上产生的一些图。屏幕关闭，但不会清零，终止此功能。
参见----------See Also----------
boot, jack.after.boot, print.boot
boot，jack.after.boot，print.boot
举例----------Examples----------
# We fit an exponential model to the air-conditioning data and use[我们适合指数模型的空调数据，并使用]
# that for a parametric bootstrap. Then we look at plots of the[这对于一个参数化的引导。然后，我们期待的图]
# resampled means.[重采样方法。]
air.rg <- function(data, mle) rexp(length(data), 1/mle)
air.boot <- boot(aircondit$hours, mean, R = 999, sim = "parametric",
ran.gen = air.rg, mle = mean(aircondit$hours))
plot(air.boot)
# In the difference of means example for the last two series of the [在手段例如在过去的两个系列的区别]
# gravity data[重力数据]
grav1 <- gravity[as.numeric(gravity[, 2]) >= 7, ]
grav.fun <- function(dat, w) {
strata <- tapply(dat[, 2], as.numeric(dat[, 2]))
d <- dat[, 1]
ns <- tabulate(strata)
w <- w/tapply(w, strata, sum)[strata]
mns <- as.vector(tapply(d * w, strata, sum)) # drop names[下降的名字]
mn2 <- tapply(d * d * w, strata, sum)
s2hat <- sum((mn2 - mns^2)/ns)
c(mns[2] - mns[1], s2hat)
}
grav.boot <- boot(grav1, grav.fun, R = 499, stype = "w", strata = grav1[, 2])
plot(grav.boot)
# now suppose we want to look at the studentized differences.[现在假设我们想看看在学生化差异。]
grav.z <- (grav.boot$t[, 1]-grav.boot$t0[1])/sqrt(grav.boot$t[, 2])
plot(grav.boot, t = grav.z, t0 = 0)
# In this example we look at the one of the partial correlations for the[在这个例子中，我们期待在为部分相关]
# head dimensions in the dataset frets.[DataSet中的苦恼头尺寸。]
frets.fun <- function(data, i) {
pcorr <- function(x) {
# Function to find the correlations and partial correlations between[函数来查找相关和部分相关关系]
# the four measurements.[四个测量。]
v <- cor(x)
v.d <- diag(var(x))
iv <- solve(v)
iv.d <- sqrt(diag(iv))
iv <- - diag(1/iv.d) %*% iv %*% diag(1/iv.d)
q <- NULL
n <- nrow(v)
for (i in 1 n-1))
q <- rbind( q, c(v[i, 1:i], iv[i,(i+1):n]) )
q <- rbind( q, v[n, ] )
diag(q) <- round(diag(q))
q
}
d <- data[i, ]
v <- pcorr(d)
c(v[1,], v[2,], v[3,], v[4,])
}
frets.boot <- boot(log(as.matrix(frets)), frets.fun, R = 999)
plot(frets.boot, index = 7, jack = TRUE, stinf = FALSE, useJ = FALSE)
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 2012-2-17 10:21:30
