Spatial location(SpatialNP)
Spatial location()所属R语言包：SpatialNP
Multivariate location estimates based on spatial signs and signed ranks
多元分布的位置，根据空间的标志和符号秩估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Iterative algorithms to find spatial median, multivariate Hodges-Lehmann estimate of
发现空间的中位数，多元霍奇斯莱曼估计迭代算法
用法----------Usage----------
spatial.location(X, score = c("sign", "signrank"), init = NULL,
shape = TRUE, steps = Inf, maxiter = 500, eps = 1e-6,
na.action = na.fail)
ae.spatial.median(X, init = NULL, shape = TRUE, steps = Inf,
maxiter = 500, eps = 1e-6, na.action = na.fail)
ae.hl.estimate(X, init = NULL, shape = TRUE, steps = Inf,
maxiter = 500, eps = 1e-06, na.action = na.fail)
参数----------Arguments----------
参数：X
a matrix or a data frame
一个矩阵或一个数据框
参数：score
a character string indicating which transformation of the observations should be used
改造的意见，应使用一个字符串，指示
参数：init
an optional vector giving the initial point of the iteration
一个可选的矢量给出的初始点的迭代
参数：shape
logical, or a matrix. See details
逻辑，或矩阵。查看详细资料
参数：steps
fixed number of iteration steps to take, if Inf iteration is repeated until convergence (or until maxiter steps)
固定数量的迭代步数，如果Inf重复迭代，直到收敛（或直到maxiter步骤）
参数：eps
tolerance for convergence
容忍收敛
参数：maxiter
maximum number of iteration steps
最大迭代步数
参数：na.action
a function which indicates what should happen when the data contain 'NA's. Default is to fail.
一个函数，它表示时会发生什么数据包含“NA”。默认是要失败的。
Details
详细信息----------Details----------
Spatial median and Hodges-Lehmann estimator (spatial median of the pairwise differences) are not affine equivariant. Affine equivariance can be achieved by simultaneously estimating the corresponding shape, as proposed for the spatial median by Hettmansperger and Randles (2002). For spatial median the corresponding shape is signs.shape and for the Hodges-Lehmann estimate it is signrank.shape.
空间中位数和霍奇斯-莱曼估计（空间成对的差异中位数）仿射等变化。仿射equivariance同时估计相应的形状，可以通过以下来实现，，提出由Hettmansperger和兰德尔斯的空间中位数（2002）。空间中位数相对应的形状signs.shape和霍奇斯莱曼估计是signrank.shape。
spatial.location is a wrapper function for a unified access to both location estimates. The choice of estimate is done via score:
spatial.location是一个包装函数为一个统一的访问这两个位置估计。估计的选择是通过score：
"sign" for spatial median
"sign"的空间中位数
"signrank" for Hodges-Lehmann estimate
"signrank"霍奇斯 - 莱曼估计
If a matrix (must be symmetric and positive definite, but this is not checked) is given as shape the location estimate is found with respect to that shape and no further shape estimation is done. If a logical TRUE is given as shape the shape is estimated and consequently the affine equivariant version of the location estimate is found. If shape is FALSE then shape estimation is not done and the non affine equivariant versions of the location estimate, that is the spatial median and the Hodges-Lehmann estimate are found.
如果一个矩阵（必须是对称正定的，但是这不是选中）被给定为shape的位置估计发现相对于该形状，并且没有进一步的形状推定。如果一个逻辑TRUE的shape的形状估计，因此仿射同变版本的位置估计。如果shape是FALSE然后形状推定还没有做，被发现的位置估计，即是空间的中位数和霍奇斯莱曼估计非仿射等变版本。
值----------Value----------
The estimate vector with the (final estimate of or given) shape matrix as attribute "shape".
（最后估计）型矩阵的属性"shape"估计向量。
（作者）----------Author(s)----------
Seija Sirkia, <a href="mailto:seija.sirkia@iki.fi">seija.sirkia@iki.fi</a>, Jari Miettinen, <a href="mailto:jari.p.miettinen@jyu.fi">jari.p.miettinen@jyu.fi</a>
参考文献----------References----------
<h3>See Also</h3>
实例----------Examples----------
A<-matrix(c(1,2,-3,4,3,-2,-1,0,4),ncol=3)
X<-matrix(rnorm(3000),ncol=3)%*%t(A)
spatial.location(X,score="signrank")
spatial.location(X,score="sign")
#compare with:[对比：]
colMeans(X)
ae.hl.estimate(X,shape=A%*%t(A))
ae.hl.estimate(X,shape=FALSE)
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 2012-9-30 12:49:16
