Normalizes the empirical distribution of a set of samples to a target distribution
标准化的一组样本的经验分布到目标分布
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Normalizes the empirical distribution of a set of samples to a target distribution. The samples may differ in size.
标准化的一组样本的经验分布到目标分布。样本大小可能会有所不同。
用法----------Usage----------
参数----------Arguments----------
参数:X
a list with numeric vectors. The vectors may be of different lengths.
listnumericvector的。 vectors可能是不同的长度。
参数:xTarget
The target empirical distribution. If NULL, the target distribution is calculated as the average empirical distribution of the samples.
目标的经验分布。如果NULL,目标分布计算的平均样本的经验分布。
参数:...
Passed to normalizeQuantileSpline.numeric().
传递normalizeQuantileSpline.numeric()。
值----------Value----------
Returns a list of normalized numeric vector of the same lengths as the corresponding ones in the input matrix.
返回一个归listnumeric相同的长度作为输入矩阵中相应的。vector
遗漏值----------Missing values----------
Missing values are excluded. Values that are NA remain NA after normalization. No new NAs are introduced.
遗漏值被排除在外。值是NA保持NA后标准化。没有新的NA的介绍。
作者(S)----------Author(s)----------
Henrik Bengtsson, Statistics Department,
University of California at Berkeley.
参见----------See Also----------
The target empirical distribution is calculated as the average using *averageQuantile(). Each vector is normalized toward this target disribution using normalizeQuantileSpline.numeric(). *normalizeQuantileRank().
作为使用*averageQuantile()平均计算目标的经验分布。每个vector归朝这个目标disribution使用normalizeQuantileSpline.numeric()。 *normalizeQuantileRank()。