boot.array(boot)
boot.array()所属R语言包：boot
Bootstrap Resampling Arrays
引导重采样阵列
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function takes a bootstrap object calculated by one of the functions boot, censboot, or tilt.boot and returns the frequency (or index) array for the bootstrap resamples.
此功能需要一个引导对象的功能之一计算boot，censboot或tilt.boot和回报的频率（或指数）为引导重新采样阵列。
用法----------Usage----------
boot.array(boot.out, indices)
参数----------Arguments----------
参数：boot.out
An object of class "boot" returned by one of the generation functions for such an object.
一个类的对象"boot"返回了这样一个对象生成功能之一。
参数：indices
A logical argument which specifies whether to return the frequency array or the raw index array. The default is indices=FALSE unless boot.out was created by tsboot in which case the default is indices=TRUE. </table>
逻辑参数指定是否返回的频率数组或原料的索引数组。默认是indices=FALSE除非boot.outtsboot在这种情况下，默认的是indices=TRUE创建。 </ TABLE>
Details
详情----------Details----------
The process by which the original index array was generated is repeated with the same value of .Random.seed. If the frequency array is required then freq.array is called to convert the index array to a frequency array.
重复使用相同的值.Random.seed原来的索引数组生成过程。如果需要，那么频率阵列freq.array被称为转换频率数组的索引数组。
A resampling array can only be returned when such a concept makes sense. In particular it cannot be found for any parametric or model-based resampling schemes. Hence for objects generated by censboot the only resampling scheme for which such an array can be found is ordinary case resampling. Similarly if boot.out$sim is "parametric" in the case of boot or "model" in the case of tsboot the array cannot be found. Note also that for post-blackened bootstraps from tsboot the indices found will relate to those prior to any post-blackening and so will not be useful.
重新取样阵列只能返回时，这样的概念是有意义的。特别是，它无法找到任何参数或模型为基础的重采样计划。因此censboot只重采样计划，可以发现这样的一个数组生成的对象是普通的情况下重新取样。同样，如果boot.out$sim是"parametric"boot或"model"在tsboot数组不能被发现的情况下的。还要注意后变黑从白手起家tsboot指数发现，将涉及到那些之前任何职位发黑，所以不会是有用的。
Frequency arrays are used in many post-bootstrap calculations such as the jackknife-after-bootstrap and finding importance sampling weights. They are also used to find empirical influence values through the regression method.
使用频率阵列在许多后引导，如计算后的折刀，引导和发现的重要性采样重量。他们还通过回归方法用来寻找经验的影响值。
值----------Value----------
A matrix with boot.out$R rows and n columns where n is the number of observations in boot.out$data. If indices is FALSE then this will give the frequency of each of the original observations in each bootstrap resample. If indices is TRUE it will give the indices of the bootstrap resamples in the order in which they would have been passed to the statistic.
与boot.out$R行n列的矩阵，其中n是观测boot.out$data的数量。如果indices是FALSE那么这将让每一个在每个引导重采样的原始观测的频率。如果indices是TRUE它会给引导在其中，他们将被传递到统计的顺序重新采样指数。
副作用----------Side Effects----------
This function temporarily resets .Random.seed to the value in boot.out$seed and then returns it to its original value at the end of the function.
此功能暂时重置.Random.seedboot.out$seed值，然后返回到其原始值在函数的末尾。
参见----------See Also----------
boot, censboot, freq.array, tilt.boot, tsboot
boot，censboot，freq.array，tilt.boot，tsboot
举例----------Examples----------
# A frequency array for a nonparametric bootstrap[一个非参数引导的频率数组]
city.boot <- boot(city, corr, R = 40, stype = "w")
boot.array(city.boot)
perm.cor <- function(d,i) cor(d$x,d$u[i])
city.perm <- boot(city, perm.cor, R = 40, sim = "permutation")
boot.array(city.perm, indices = TRUE)
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 2012-2-16 19:26:35
