control(boot)
control()所属R语言包：boot
Control Variate Calculations
控制变量的计算
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will find control variate estimates from a bootstrap output object. It can either find the adjusted bias estimate using post-simulation balancing or it can estimate the bias, variance, third cumulant and quantiles, using the linear approximation as a control variate.
此功能将找到一个引导输出对象的控制变量的估计。它可以使用后仿真平衡或调整偏置估计，它可以作为控制变量，采用线性近似估计的偏差，方差，第三累积和位数。
用法----------Usage----------
control(boot.out, L = NULL, distn = NULL, index = 1, t0 = NULL,
t = NULL, bias.adj = FALSE, alpha = NULL, ...)
参数----------Arguments----------
参数：boot.out
A bootstrap output object returned from boot. The bootstrap replicates must have been generated using the usual nonparametric bootstrap.
从boot返回引导输出对象。引导复制必须已使用通常的非参数引导产生。
参数：L
The empirical influence values for the statistic of interest. If L is not supplied then empinf is called to calculate them from boot.out.
利益的统计经验的影响值。如果L没有提供，则empinf被称为计算boot.out的他们。
参数：distn
If present this must be the output from smooth.spline giving the distribution function of the linear approximation. This is used only if bias.adj is FALSE. Normally this would be found using a saddlepoint approximation. If it is not supplied in that case then it is calculated by saddle.distn.
如果存在，这一定是从smooth.spline线性近似分布函数的输出。这是只有bias.adj是FALSE。这通常被发现使用鞍点逼近。如果是在这种情况下不提供的，那么它的计算方法是saddle.distn。
参数：index
The index of the variable of interest in the output of boot.out$statistic.
该指数的兴趣在boot.out$statistic输出变量。
参数：t0
The observed value of the statistic of interest on the original data set boot.out$data. This argument is used only if bias.adj is FALSE. The input value is ignored if t is not also supplied. The default value is is boot.out$t0[index].
利益的统计原始数据的观测值设定boot.out$data。这种说法是用来只有bias.adj是FALSE。 t如果是不是也提供输入值将被忽略。默认值是boot.out$t0[index]。
参数：t
The bootstrap replicate values of the statistic of interest. This argument is used only if bias.adj is FALSE. The input is ignored if t0 is not supplied also. The default value is boot.out$t[,index].
引导复制利益的统计值。这种说法是用来只有bias.adj是FALSE。 t0如果也没有提供输入被忽略。默认值是boot.out$t[,index]。
参数：bias.adj
A logical variable which if TRUE specifies that the adjusted bias estimate using post-simulation balance is all that is required. If bias.adj is FALSE (default) then the linear approximation to the statistic is calculated and used as a control variate in estimates of the bias, variance and third cumulant as well as quantiles.
一个逻辑变量，如果TRUE指定使用后模拟平衡的调整偏差估计是所有需要。如果bias.adj是FALSE（默认），然后线性近似的统计计算，作为控制变量的偏差，方差和第三累积以及位数估计。
参数：alpha
The alpha levels for the required quantiles if bias.adj is FALSE.
α水平所需的位数bias.adj如果是FALSE。
参数：...
Any additional arguments that boot.out$statistic requires. These are passed unchanged every time boot.out$statistic is called. boot.out$statistic is called once if bias.adj is TRUE, otherwise it may be called by empinf for empirical influence calculations if L is not supplied.
任何额外的参数，boot.out$statistic需要。这些都是通过不变的每boot.out$statistic被称为时间。 boot.out$statistic被称为一次如果bias.adj是TRUE，否则可能会empinf如果经验的影响计算L不提供调用。
Details
详情----------Details----------
If bias.adj is FALSE then the linear approximation to the statistic is found and evaluated at each bootstrap replicate. Then using the equation T* = Tl*+(T*-Tl*), moment estimates can be found. For quantile estimation the distribution of the linear approximation to t is approximated very accurately by saddlepoint methods, this is then combined with the bootstrap replicates to approximate the bootstrap distribution of t and hence to estimate the bootstrap quantiles of t.
如果bias.adj是FALSE然后线性近似的统计发现，在每个引导重复计算。然后用公式T *的= TL *（T *的铊*），矩估计可以找到。位数估计的线性近似分布t近似鞍点方法非常准确，这是结合引导复制到近似t引导分布，因此估计引导位数t。
值----------Value----------
If bias.adj is TRUE then the returned value is the adjusted bias estimate.
如果bias.adj是TRUE然后返回的值是调整后的偏差估计。
If bias.adj is FALSE then the returned value is a list with the following components
如果bias.adj是FALSE然后返回值是一个具有下列组件的列表
参数：L
The empirical influence values used. These are the input values if supplied, and otherwise they are the values calculated by empinf.
使用经验的影响值。这些输入值，如果提供的，否则他们是empinf计算值。
参数：tL
The linear approximations to the bootstrap replicates t of the statistic of interest.
引导线性近似复制利益的统计t。
参数：bias
The control estimate of bias using the linear approximation to t as a control variate.
偏差控制使用t作为一个控制变量的线性近似估计。
参数：var
The control estimate of variance using the linear approximation to t as a control variate.
控制使用线性近似t作为一个控制变量方差的估计。
参数：k3
The control estimate of the third cumulant using the linear approximation to t as a control variate.
第三累积使用t作为一个控制变量的线性近似的控制预算。
参数：quantiles
A matrix with two columns; the first column are the alpha levels used for the quantiles and the second column gives the corresponding control estimates of the quantiles using the linear approximation to t as a control variate.
一个具有两列，第一列矩阵位数的α水平和第二列给出了相应的控制使用t作为一个控制变量的线性近似位数的估计。
参数：distn
An output object from smooth.spline describing the saddlepoint approximation to the bootstrap distribution of the linear approximation to t. If distn was supplied on input then this is the same as the input otherwise it is calculated by a call to saddle.distn.
从输出对象smooth.spline描述t线性近似的引导分布的鞍点逼近。如果distn然后输入提供，这是作为输入相同，否则将被计算由saddle.distn调用。
参考文献----------References----------
Bootstrap Methods and Their Application. Cambridge University Press.
simulation. Biometrika, 73, 555–566.
Journal of the American Statistical Association, 55, 79–89.
参见----------See Also----------
boot, empinf, k3.linear, linear.approx, saddle.distn, smooth.spline, var.linear
boot，empinf，k3.linear，linear.approx，saddle.distn，smooth.spline，var.linear
举例----------Examples----------
# Use of control variates for the variance of the air-conditioning data[用于控制变元的空调数据的方差]
mean.fun <- function(d, i)
{ m <- mean(d$hours[i])
n <- nrow(d)
v <- (n-1)*var(d$hours[i])/n^2
c(m, v)
}
air.boot <- boot(aircondit, mean.fun, R = 999)
control(air.boot, index = 2, bias.adj = TRUE)
air.cont <- control(air.boot, index = 2)
# Now let us try the variance on the log scale.[现在，让我们尝试日志尺度上的变异。]
air.cont1 <- control(air.boot, t0 = log(air.boot$t0[2]),
t = log(air.boot$t[, 2]))
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 2012-2-16 20:41:08
