scaleTau2(robustbase)
scaleTau2()所属R语言包：robustbase
Robust Tau-Estimate of Scale
强大的规模估计的头
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the robust τ-estimate of univariate scale, as proposed by Maronna and Zamar (2002); improved by a consistency factor.
计算强劲的τ估计的单变量规模的建议，由Maronna和Zamar（2002）;提高一致性因素。
用法----------Usage----------
scaleTau2(x, c1 = 4.5, c2 = 3.0, consistency = TRUE,
mu.too = FALSE, ...)
参数----------Arguments----------
参数：x
numeric vector
数字矢量
参数：c1,c2
non-negative numbers, specifying cutoff values for the biweighting of the mean and the rho function respectively.
非负数，指定的截止值分别的biweighting的均值和rho沸石功能。
参数：mu.too
logical indicating if both location and scale should be returned or just the scale (when mu.too=FALSE as by default).
逻辑的位置和规模，应退回或只是规模（当mu.too=FALSE，因为默认情况下）。
参数：consistency
logical indicating if the consistency correction factor (for the scale) should be applied.
逻辑指示是否应适用的一致性校正因子（规模）。
参数：...
potentially additional arguments which are not used.
潜在的额外的参数，这些参数不使用。
Details
详细信息----------Details----------
First, s0 := MAD, i.e. the equivalent of mad(x, constant=1) is computed. Robustness weights w_i := w_{c1}((x_i - med(X))/ s_0) are computed, where w_c(u) = max(0, (1 - (u/c)^2)^2). The robust location measure is defined as μ(X) := (∑_i w_i x_i)/(∑_i w_i), and the robust tau-estimate is s(X)^2 := s_0^2 * (1/n) ∑_i ρ_{c2}((x_i - μ(X))/s_0), where ρ_c(u) = min(c^2, u^2). <br> scaleTau2(*, consistency=FALSE) returns s(X), whereas this value is divided by its asymptotic limit when consistency = TRUE as by default.
首先，s0：= MAD，即相当于mad(x, constant=1)计算。鲁棒性的权重w_i := w_{c1}((x_i - med(X))/ s_0)计算，其中w_c(u) = max(0, (1 - (u/c)^2)^2)。坚固耐用的位置测量被定义为μ(X) := (∑_i w_i x_i)/(∑_i w_i)，，，强劲的tau估计是s(X)^2 := s_0^2 * (1/n) ∑_i ρ_{c2}((x_i - μ(X))/s_0)，其中ρ_c(u) = min(c^2, u^2)。参考scaleTau2(*, consistency=FALSE)返回s(X)，而此值除以的渐近极限时consistency = TRUE因为默认情况下。
Note that for n = length(x) == 2, all equivariant scale estimates are proportional, and specifically, scaleTau2(x, consistency=FALSE) == mad(x, constant=1). See also the reference.
请注意，n = length(x) == 2，所有等变规模估计是成比例的，并且具体地，scaleTau2(x, consistency=FALSE) == mad(x, constant=1)。也参看参考。
值----------Value----------
numeric vector of length one (if mu.too is FALSE as by default) or two (when mu.too = TRUE) with robust scale or (location,scale) estimators s^(x) or (m^(x), s^(x)).
数字矢量的长度为一（mu.too如果是FALSE时，默认情况下）或两个（mu.too = TRUE）具有强大的规模（地点，规模）估计s^(x)或(m^(x), s^(x))。
（作者）----------Author(s)----------
Original by Kjell Konis with substantial modifications by
Martin Maechler.
参考文献----------References----------
Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307–317.
参见----------See Also----------
Sn, Qn, mad; further covOGK for which scaleTau2 was designed.
Sn，Qn，mad进一步covOGKscaleTau2的设计。
实例----------Examples----------
x <- c(1:7, 1000)
sd(x) # non-robust std.deviation[非强大的std.deviation的]
scaleTau2(x)
scaleTau2(x, mu.too = 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。
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 2012-9-27 22:14:43
