dissassoc(TraMineR)
dissassoc()所属R语言包：TraMineR
Analysis of discrepancy from dissimilarity measures
相异措施的差异分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute and test the share of discrepancy (defined from a dissimilarity matrix) explained by a categorical variable.
分类变量计算和测试的份额差异（从相异度矩阵定义）来解释。
用法----------Usage----------
dissassoc(diss, group, weights=NULL, R=1000,
weight.permutation="replicate", squared=FALSE)
参数----------Arguments----------
参数：diss
A dissimilarity matrix or a dist object (see dist)
一个的相异矩阵或一个dist对象（见dist）
参数：group
The grouping variable
分组变量
参数：weights
optional numerical vector containing weights.
可选的数值向量中的权重。
参数：R
Number of permutations for computing the p-value. If equal to 1, no permutation test is performed.
用于计算p-值的排列数目。如果等于1，没有置换检验进行。
参数：weight.permutation
Weighted permutation method: "diss" (attach weights to the dissimilarity matrix), "replicate" (replicate case using weights), "rounded-replicate" (replicate case using rounded weights), "random-sampling" (random assignment of covariate profiles to the objects using distributions defined by the weights.)
加权置换的方法："diss"（附加的相异度矩阵的权重），"replicate"（复制的情况下使用weights）"rounded-replicate"（复制的情况下使用四舍五入weights） "random-sampling"（协的对象所定义的权重分布中随机分配的。）
参数：squared
Logical. If TRUE the dissimilarities diss are squared.
逻辑。如果TRUE的异同diss的平方。
Details
详细信息----------Details----------
The dissassoc function assesses the association between objects characterized by their dissimilarity matrix and a discrete covariate. It provides a generalization of the ANOVA principle to any kind of distance metric. The function returns a pseudo R-square that can be interpreted as a usual R-square. The statistical significance of the association is computed by means of permutation tests. The function performs also a test of discrepancy homogeneity (equality of within variances) using a generalization of the Levene statistic and Bartlett's statistics. <br> There are print and hist methods (the latter producing an histogram of the permuted values used for testing the significance).
dissassoc功能评估他们的的相异矩阵和一个离散的协变量特征的对象之间的关联。它提供了一个普遍化的ANOVA原则，任何形式的距离度量。该函数返回一个的伪R-平方可以理解为通常的R-平方。的关联的统计显着性的计算通过置换试验。该函数执行的差异同质性（内差异的平等）使用的列文的统计和Bartlett统计的泛化也是一个考验。 <br>文章有print和hist方法（后者产生直方图的置换后的值，用于测试的意义）。
值----------Value----------
An object of class dissassoc with the following components:
对象的类dissassoc以下组件：
参数：groups
A data frame with the number of cases and the discrepancy of each group
一个数据框的病例数和各组的差异
参数：anova.table
The pseudo ANOVA table
伪方差分析表
参数：stat
The value of the statistics and their p-values
的统计值和p值
参数：perms
The permutation object, containing the values computed for each permutation
的置换的对象，包含计算出的值的每个置换
参考文献----------References----------
Discrepancy analysis of complex objects using dissimilarities. In F. Guillet, G. Ritschard, H. Briand, and D. A. Zighed (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.
Austral Ecology 26, 32–46.
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> disstree for an induction tree analyse of objects characterized by a dissimilarity matrix. <br> disscenter to compute the distance of each object to its group center from pairwise dissimilarities. <br> dissmfac to perform multi-factor analysis of variance from pairwise dissimilarities.
dissvar的来计算的伪方差的异同和伪方差分析概念的基本介绍。参考disstree感应树分析相异度矩阵的特征的对象。参考disscenter计算两两相异的每个对象组中心的距离。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")
## R=1 implies no permutation test[＃R = 1，意味着没有置换测试]
da <- dissassoc(mvad.ham, group=mvad$gcse5eq, R=10)
print(da)
hist(da)
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 11:33:11
