mosaicMiss(VIM)
mosaicMiss()所属R语言包：VIM
Mosaic plot with information about missing/imputed values
马赛克的图与信息丢失/估算值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Create a mosaic plot with information about missing/imputed values.
创建一个马赛克图信息丢失/估算值。
用法----------Usage----------
mosaicMiss(x, delimiter = NULL, highlight = NULL, selection = c("any",
"all"), plotvars = NULL, col = c("skyblue","red","orange"),
labels = NULL, miss.labels = TRUE, ...)
参数----------Arguments----------
参数：x
a matrix or data.frame.
矩阵或data.frame。
参数：delimiter
a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, x needs to have colnames). If given, it is used to determine the corresponding imputation-index for any imputed variable (a logical-vector indicating which values of the variable have been imputed). If such imputation-indices are found, they are used for highlighting and the colors are adjusted according to the given colors for imputed variables (see col).
一个特征向量来区分变量和插补指数估算的变量（因此，x需要有colnames）。如果给出，它被用来确定相应的插补索引的任何估算的变量（一个逻辑矢量指示变量的值已被插补）。如果这样的归集指数被发现，它们用于高亮和颜色的调整，根据给定的颜色估算变量（见col“）。
参数：highlight
a vector giving the variables to be used for highlighting. If NULL (the default), all variables are used for highlighting.
一个向量给要用于高亮显示的变量。如果NULL（默认值），所有的变量都用于突出显示。
参数：selection
the selection method for highlighting missing/imputed values in multiple highlight variables. Possible values are "any" (highlighting of missing/imputed values in any of the highlight variables) and "all" (highlighting of missing/imputed values in all of the highlight variables).
突出丢失/估算值多个亮点变量的选择方法。可能的值是"any"（突出显示缺少/在任何的亮点变量的估算值）和"all"（突出的丢失/估算值的所有的亮点变量）。
参数：plotvars
a vector giving the categorical variables to be plotted. If NULL (the default), all variables are plotted.
提供分类变量要绘制一个矢量。如果NULL（默认值），所有变量都被绘制。
参数：col
a vector of length three giving the colors to be used for observed, missing and imputed data. If only one color is supplied, the tiles corresponding to observed data are transparent and the supplied color is used for highlighting.
一个长度为3的向量提供的颜色被用于观察，缺少和估算的数据。如果只有一种颜色被提供时，观察到的数据对应的瓦片是透明的，和所提供的颜色的用于高亮显示。
参数：labels
a list of arguments for the labeling function labeling_border.
一个参数列表的标签功能labeling_border。
参数：miss.labels
either a logical indicating whether labels should be plotted for observed and missing/imputed (highlighted) data, or a character vector giving the labels.
无论是逻辑，指示是否应绘制标签的观察和失踪/估算（高亮）的数据或字符矢量提供的标签。
参数：...
additional arguments to be passed to mosaic.
额外的参数传递给mosaic。
Details
详细信息----------Details----------
Mosaic plots are graphical representations of multi-way contingency tables. The frequencies of the different cells are visualized by area-proportional rectangles (tiles). Additional tiles are be used to display the frequencies of missing/imputed values. Furthermore, missing/imputed values in a certain variable or combination of variables can be highlighted in order to explore their structure.
多路列联表马赛克图的图形表示。不同的单元的频率是可视化的区域的比例矩形（瓷砖）。其他瓷砖可用于显示频率的丢失/估算值。此外，突出表现在缺少/估算值在某个变量或变量组合，以探讨其结构。
值----------Value----------
An object of class "structable" is returned invisibly.
一个对象的类"structable"的返回无形。
注意----------Note----------
This function uses the highly flexible strucplot framework of package vcd.
此功能使用高度灵活的strucplot框架包vcd。
（作者）----------Author(s)----------
Andreas Alfons, modifications by Bernd Prantner
参考文献----------References----------
Visualizing multi-way contingency tables with <code>vcd</code>. Journal of Statistical Software, 17 (3), 1–48.
Exploring incomplete data using visualization tools. Journal of Advances in Data Analysis and Classification, Online first. DOI: 10.1007/s11634-011-0102-y.
参见----------See Also----------
spineMiss, mosaic
spineMiss，mosaic
实例----------Examples----------
data(sleep, package = "VIM")
## for missing values[＃遗漏值]
mosaicMiss(sleep, highlight = 4,
plotvars = 8:10, miss.labels = FALSE)
## for imputed values[＃估算值]
mosaicMiss(kNN(sleep), highlight = 4,
plotvars = 8:10, delimiter = "_imp", miss.labels = 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 2012-10-1 16:06:52
