Take a matrix of indices for nonparametric bootstrap resamples and return the frequencies of the original observations in each resample.
采取非参数的bootstrap重新取样指数矩阵，并在每个重采样返回原始观测频率。
用法----------Usage----------
freq.array(i.array)
参数----------Arguments----------
参数：i.array
This will be an matrix of integers between 1 and n, where n is the number of observations in a data set. The matrix will have n columns and R rows where R is the number of bootstrap resamples. Such matrices are found by boot when doing nonparametric bootstraps. They can also be found after a bootstrap has been run through the function boot.array. </table>
这将是一个1到n，其中n是观测数据集之间的整数矩阵。矩阵将有n列r行，其中R是引导重新采样的数量。这样矩阵boot做非参数白手起家的。它们也可以被发现后，引导已通过函数boot.array运行。 </ TABLE>
值----------Value----------
A matrix of the same dimensions as the input matrix. Each row of the matrix corresponds to a single bootstrap resample. Each column of the matrix corresponds to one of the original observations and specifies its frequency in each bootstrap resample. Thus the first column tells us how often the first observation appeared in each bootstrap resample. Such frequency arrays are often useful for diagnostic purposes such as the jackknife-after-bootstrap plot. They are also necessary for the regression estimates of empirical influence values and for finding importance sampling weights.
输入矩阵的尺寸相同的矩阵。矩阵的每一行对应一个单一的bootstrap重采样。矩阵的每一列对应一个原始观测，并指定其频率在每个引导重采样。因此，第一列告诉我们如何往往先观察出现在每个引导重采样。如刀切后，引导图的诊断目的，这样的频率阵列往往是有用的。他们还需要经验的影响值的回归估计和发现的重要性采样重量。
发表于 2012-2-16 18:49:05
