disscenter(TraMineR)
disscenter()所属R语言包：TraMineR
Compute distances to the center of a group
计算距离的中心的一组
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the dissimilarity between objects and their group center from their pairwise dissimilarity matrix.
计算对象之间的差异性和组中心从他们的两两相异度矩阵。
用法----------Usage----------
disscenter(diss, group=NULL, medoids.index=NULL,
allcenter = FALSE, weights=NULL, squared=FALSE)
参数----------Arguments----------
参数：diss
a dissimilarity matrix such as generated by seqdist, or a dist object (see dist)
一个相异度矩阵如产生的seqdist，或dist对象（见dist）
参数：group
if NULL (default), the whole data set is considered. Otherwise a different center is considered for each distinct value of the group variable
如果NULL（默认），被认为是整个数据集。否则，不同的中心被认为是为每个不同的组变量值的
参数：medoids.index
if NULL, returns the dissimilarity to the center. If set to "first", returns the index of the first encountered most central sequence. If group is set, an index is returned per group. When set to "all", indexes of all medoids (one list per group) are returned.
如果NULL，返回相异的中心。如果设置为"first"，返回索引的第一个遇到的最核心的序列。如果group设置，索引每个组返回。当设置为"all"，索引的所有中心点（每个组的一个列表）被返回。
参数：allcenter
logical. If TRUE, returns a data.frame containing the dissimilarity between each object and its group center, each column corresponding to a group.
逻辑。如果TRUE，返回一个data.frame包含对象之间的差异性及其集团中心，各列对应的一组。
参数：weights
optional numerical vector containing weights.
可选的数值向量中的权重。
参数：squared
Logical. If TRUE diss is squared.
逻辑。如果TRUEdiss平方。
Details
详细信息----------Details----------
This function computes the dissimilarity between given objects and their group center. It is possible that the group center does not belong to the space formed by the objects (in the same way as the average of integer numbers is not necessarily an integer itself). This distance can also be understood as the contribution to the discrepancy (see dissvar). Note that when the dissimilarity measure does not respect the triangle inequality, the dissimilarity between a given object and its group center may be negative
此函数计算给定的对象之间的差异性及其组中心。这是可能的组中心不属于的对象所形成的空间内（以同样的方式作为整数的平均值不一定的整数本身）。这个距离也可以被理解为的贡献的差异（见dissvar）。请注意，当相异措施不尊重三角不等式，一个给定的对象和它的集团中心之间的相异可能为负
It can be shown that this dissimilarity is equal to (see <CITE>Batagelj 1988</CITE>):
它可以被显示，这相异等于（见<CITE> Batagelj </ CITE> 1988年）：
where SS is the sum of squares (see dissvar).
SS的平方（见dissvar）。
值----------Value----------
A vector with the dissimilarity to the group center for each object, or a list of medoid indexes.
一个向量组中心的每一个对象，或一个的medoid索引列表的分辨率不同。
参考文献----------References----------
Discrepancy analysis of complex objects using dissimilarities. In F. Guillet, G. Ritschard, D. A. Zighed and H. Briand (Eds.), Advances in Knowledge Discovery and Management, Studies in Computational Intelligence, Volume 292, pp. 3-19. Berlin: Springer.
Analyse de dissimilarit茅s par arbre d'induction. In EGC 2009, Revue des Nouvelles Technologies de l'Information, Vol. E-15, pp. 7–18.
Classification and related methods of data analysis, Amsterdam: North-Holland, pp. 67–74.
参见----------See Also----------
dissvar to compute the pseudo variance from dissimilarities and for a basic introduction to concepts of pseudo variance analysis <br> dissassoc to test association between objects represented by their dissimilarities and a covariate. <br> disstree for an induction tree analyse of objects characterized by a dissimilarity matrix. <br> dissmfac to perform multi-factor analysis of variance from pairwise dissimilarities.
dissvar计算的伪方差相异概念的伪方差分析<BR>，的一个基本的介绍dissassoc来测试他们的不同点和协变量所代表的对象之间的关联。参考disstree感应树分析相异度矩阵的特征的对象。参考dissmfac进行多因素方差分析，两两相异。
实例----------Examples----------
## Defining a state sequence object[＃定义一个状态序列对象]
data(mvad)
mvad.seq <- seqdef(mvad[, 17:86])
## Building dissimilarities (any dissimilarity measure can be used)[＃楼异同（可用于任何相异措施）]
mvad.ham <- seqdist(mvad.seq, method="HAM")
## Compute distance to center according to group gcse5eq[计算距离中心组gcse5eq]
dc <- disscenter(mvad.ham, group=mvad$gcse5eq)
## Ploting distribution of dissimilarity to center[＃图分布的差异性为中心]
boxplot(dc~mvad$gcse5eq, col="cyan")
## Retrieving index of the first medoids, one per group[＃检索索引的第一个中心点，每一个组]
dc <- disscenter(mvad.ham, group=mvad$Grammar, medoids.index="first")
print(dc)
## Retrieving index of all medoids in each group[＃检索索引的所有中心点，各组]
dc <- disscenter(mvad.ham, group=mvad$Grammar, medoids.index="all")
print(dc)
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 2012-10-1 11:33:18
