clustvar(vegclust)
clustvar()所属R语言包：vegclust
Cluster variance (beta diversity)
方差（beta多样性）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the variation in community composition (i.e. beta diversity) found within the sites of a set of hard or fuzzy clusters.
计算群落组成（即beta多样性）的网站内找到的一组硬盘或模糊聚类的变化。
用法----------Usage----------
clustvar(x, cluster = NULL, defuzzify=FALSE,...)
参数----------Arguments----------
参数：x
Community data. Either a site-by-species matrix or a site-by-site matrix of compositional distances between sites (i.e., an object of class dist). Alternatively, this can be an object of class vegclust or vegclass, and in this case it is unnecessary to provide cluster.
社区数据。无论是网站的物种矩阵或一个站点的站点矩阵的成分站点之间的距离（即一个对象类dist“）。可替代地，这可以是一个对象的类vegclust或vegclass，并在这种情况下，这是不必要的提供cluster的。
参数：cluster
A vector indicating the hard membership of each object in x to a set of groups.
一个向量表明该硬盘x一套班子成员中的每个对象的。
参数：defuzzify
A flag indicating whether fuzzy memberships should be defuzzified (see function defuzzify). Only applies to the case where an object of class vegclust or vegclass is supplied in x.
一个标志，指示模糊的会员资格是否应解模糊（见功能defuzzify）。仅适用于类的一个对象vegclust或vegclass提供x的情况。
参数：...
Additional parameters for function defuzzify.
其他参数功能defuzzify。
Details
详细信息----------Details----------
If an object of class vegclust or vegclass is provided as input, the function uses the information contained there (distances to clusters, memberships and exponent of fuzziness) in order to compute cluster variances. Both mobile and fixed clusters are considered. Membership matrices may be defuzzified if defuzzify=TRUE. Alternatively, if x is a data matrix (site by species or distances among sites) and cluster is null, the function assumes a single cluster of all points in x. When cluster is provided, the function computes cluster variance for each (hard) group and this computation implies setting the centroid of the group. In contrast, when an object of class vegclust or vegclass is provided the centroids do not need to be recomputed, and the distances to centroids are used directly.
如果一个类的对象vegclust或vegclass作为输入提供，该函数使用所包含的信息有（距离聚类，成员资格和指数的模糊性），以计算聚类的差异。被认为是移动和固定的聚类。会员矩阵解模糊，如果defuzzify=TRUE。另外，如果x是一个数据矩阵（网站的物种或站点之间的距离）和cluster是null，函数假定一个单一聚类中所有点的x。当cluster提供，该函数为每个组（硬）计算方差计算意味着本集团的重心。相反，当类的一个对象vegclust或vegclass提供不需要重新计算的重心，以及重心的距离直接使用。
值----------Value----------
A double value (for one cluster) or a vector of values, one per each cluster.
一个double值（一个聚类）或一个向量的值，每一个每一个聚类。
（作者）----------Author(s)----------
Miquel De C谩ceres, Forest Science Center of Catalonia
参见----------See Also----------
vegclust, kmeans,defuzzify
vegclust，kmeans，defuzzify
实例----------Examples----------
# Loads data [数据加载]
data(wetland)
# This equals the chord transformation (see also 'normalize' option in \code{\link{decostand}} from the vegan package)[这等于和弦转换（参见标准化选项\ {\的链接{decostand}}从素食包的代码）]
wetland.chord = as.data.frame(sweep(as.matrix(wetland), 1, sqrt(rowSums(as.matrix(wetland)^2)), "/"))
# Create noise clustering with 3 clusters. Perform 10 starts from random seeds and keep the best solution[创建噪音聚类与3类。进行10次随机种子开始，并保持最佳的解决方案]
wetland.nc = vegclust(wetland.chord, mobileCenters=3, m = 1.2, dnoise=0.75, method="NC", nstart=10)
# Gets cluster variance of fuzzy clusters[获取方差的模糊聚类]
clustvar(wetland.nc)
# Gets cluster variance of fuzzy clusters after defuzzification[获取模糊化后的模糊聚类方差]
clustvar(wetland.nc, defuzzify=TRUE)
# Similar to the previous, this gets cluster variance of defuzzified (i.e. hard) clusters[类似以前的，得到方差的模糊化（即硬盘）聚类]
clustvar(wetland.chord, cluster=defuzzify(wetland.nc)$cluster)
# Gets cluster variance of K-means (i.e. hard) clusters[获取方差的K-means（即硬盘）聚类]
clustvar(wetland.chord, cluster=kmeans(wetland.chord, centers=3, nstart=10)$cluster)
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。
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发表于 2012-10-1 15:16:03
