SDCModel(SDisc)
SDCModel()所属R语言包：SDisc
SDCModel, SDisc's Cluster Model class
SDCModel，SDisc的聚类模型类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
SDCModel is the name given to SDisc Cluster Models. Subtype models from an SDisc analysis can be accessed as elements of a list, via their name or an index integer. With print, we return the mixture component (subtype) membership likelihood per sample as well as the mapping for the most likely mixture. The summary method characterizes the model in terms of odd ratio and joint distribution statistics with respect to, for instance, an confounding or verificatory factor -like gender or strata- that was
SDCModel是SDisc的簇模型的名称。亚型从SDisc分析模型也可以访问列表中的元素，通过他们的名字或索引的整数。随着print，我们返回的混合成分（亚型）的成员每个样品的可能性，以及最有可能的混合物的映射。 summary方法的模型的特点就在奇比和联合分布统计方面，例如，混淆或verificatory的因素，如性别或阶层，这是
用法----------Usage----------
## S3 method for class 'SDCModel'
print(x, data, ...)
## S3 method for class 'SDCModel'
summary(object, data, type="oddRatiosB", latex=FALSE, lab="", shortStr=FALSE, ...)
参数----------Arguments----------
参数：x
an SDCModel
SDCModel
参数：data
an SDData container
SDData容器
参数：object
an SDCModel obtained from (see SDisc and bestModel)
SDCModel获得从（见SDisc和bestModel）
参数：type
the type of summary to report, in: "oddRatios", "oddRatiosB" by default, "chi2test", "jointDistrib"
类型的总结报告，"oddRatios"，"oddRatiosB"默认情况下，"chi2test"，"jointDistrib"
参数：lab
the label of the LaTeX table
LaTeX的表的标签
参数：shortStr
whether to shorten the names of the different factors by their first letters
是否缩短的名字的第一个字母的不同因素
参数：latex
whether a LaTeX formated output should be generated
是否应该产生的LaTeX格式输出
参数：...
(currently not used) additional parameters passed to the sub-functions
（目前没有使用）额外的参数传递给这些子功能
Details
详细信息----------Details----------
print returns a matrix with G+1 columns. The G first columns represent the likelihood of each record to belong to the different mixture components. The last column corresponds the mapping of each record into one of the G components.
print返回G+1列的矩阵。 G第一列表示每个记录属于不同的混合物组分的可能性。最后一列对应的映射，每个记录的G组件之一。
summary returns different statistical summaries on a SDCModel. Among the possible summaries there are odd ratio, chi2 statistics and joint distribution with a categorical target variable. Odd ratios statistics are computed on factors of variable defined in the settings configuration file (see oddGroup in SDDataSettings). Two types of odd ratios are implemented: the oddRatios cross-product is based on counts of the number of occurence above and below the mean of the data distribution, while for oddRatiosB the effect size is used in the cross-product. Concerning chi2test and jointDistrib, they involve a comparison with a target categorical variable.
summary返回不同的统计汇总，上一个SDCModel。在可能的摘要中有奇比，χ2统计和一个明确的目标变量的联合分布。奇数比例计算统计数据的设置配置文件中定义的变量因素（见oddGroupSDDataSettings）。两种类型的奇数比率实施：oddRatios跨产品是根据发生的上面和下面的数据分布的平均值的数目的计数，而oddRatiosB的效果的大小中使用的跨产品。关于chi2test和jointDistrib，涉及目标分类变量的比较。
（作者）----------Author(s)----------
Fabrice Colas
参见----------See Also----------
modelBasedEM, SDDataSettings, texTable
modelBasedEM，SDDataSettings，texTable
实例----------Examples----------
settings <- SDDataSettings(iris)
settings['Species',] <- c(NA,FALSE, NA, NA, NA, NA)
x <- SDisc(iris, settings=settings, prefix='iris')
xBestModel <- x[[bestModel(x,1)]]
print(xBestModel, data=SDData(x))
summary(x[[bestModel(x,1)]], data=SDData(x))
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 2012-9-29 23:32:44
