CorrAn(SimultAnR)
CorrAn()所属R语言包：SimultAnR
Correspondence Analysis
对应分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The CorrAn function computes the correspondence analysis of the selected data.
CorrAn函数计算所选数据的对应分析。
用法----------Usage----------
CorrAn(data, sr = NA, sc = NA, nd = 2, dp = 2)
参数----------Arguments----------
参数：data
Data set
数据集
参数：sr
Indices of supplementary rows
行补充指标
参数：sc
Indices of supplementary columns
补充列指数
参数：nd
Number of dimensions in results
在结果中的维数
参数：dp
Number of digits in results
在结果中位数号码
Details
详细信息----------Details----------
The options sr and sc allow supplementary rows and columns to be specified.
的选项sr和sc可以补充到指定的行和列。
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>totalin </td> <td> Total inertia </td></tr> <tr valign="top"><td>eig </td> <td> Eigenvalues </td></tr> <tr valign="top"><td>resin </td> <td> Results of inertia </td></tr> <tr valign="top"><td>resi </td> <td> Results of active rows </td></tr> <tr valign="top"><td>resj </td> <td> Results of active columns </td></tr> <tr valign="top"><td>resisr </td> <td> Results of supplementary rows </td></tr> <tr valign="top"><td>resjsc </td> <td> Results of supplementary columns </td></tr> <tr valign="top"><td>X </td> <td> Matrix X </td></tr> <tr valign="top"><td>totalk </td> <td> Total of data table </td></tr> <tr valign="top"><td>I </td> <td> Number of active rows </td></tr> <tr valign="top"><td>namei </td> <td> Names of active rows </td></tr> <tr valign="top"><td>fi </td> <td> Marginal of active rows </td></tr> <tr valign="top"><td>Fs </td> <td> Projections of active rows </td></tr> <tr valign="top"><td>d2i </td> <td> Chi-square distance of active rows to their average </td></tr> <tr valign="top"><td>J </td> <td> Number of active columns </td></tr> <tr valign="top"><td>namej </td> <td> Names of active columns </td></tr> <tr valign="top"><td>fj </td> <td> Marginal of active columns </td></tr> <tr valign="top"><td>Gs </td> <td> Projections of active columns </td></tr> <tr valign="top"><td>d2j </td> <td> Chi-square distance of active columns to their average </td></tr> <tr valign="top"><td>Isr </td> <td> Number of supplementary rows </td></tr> <tr valign="top"><td>nameisr </td> <td> Names of supplementary rows </td></tr> <tr valign="top"><td>fisr </td> <td> Marginal of supplementary rows </td></tr> <tr valign="top"><td>Fssr </td> <td> Projections of supplementary rows </td></tr> <tr valign="top"><td>d2isr </td> <td> Chi-square distance of supplementary rows to the average </td></tr> <tr valign="top"><td>Xsr </td> <td> Matrix X for supplementary rows </td></tr> <tr valign="top"><td>Jsc </td> <td> Number of supplementary columns </td></tr> <tr valign="top"><td>namejsc </td> <td> Names of supplementary columns </td></tr> <tr valign="top"><td>fjsc </td> <td> Marginal of supplementary columns </td></tr> <tr valign="top"><td>Gssc </td> <td> Projections of supplementary columns </td></tr> <tr valign="top"><td>d2jsc </td> <td> Chi-square distance of supplementary columns to the average</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> totalin </ TD> <TD>总惯量</ TD> </ TR> <tr valign="top"> <TD> eig </ TD> <TD>特征值</ TD> </ TR> <tr valign="top"> <TD>resin </ TD> <TD>的惯性结果</ TD> </ TR> <tr valign="top"> <TD>resi </ TD> <TD>活动行的结果</ TD> </ TR> <TR VALIGN =“顶” > <TD> resj </ TD> <TD>结果的活动列</ TD> </ TR> <tr valign="top"> <TD> resisr </ TD> <TD >结果行补充</ TD> </ TR> <tr valign="top"> <TD>resjsc </ TD> <TD>结果的补充列</ TD> </ TR> <TR VALIGN =“”> <TD>X </ TD> <TD>矩阵X </ TD> </ TR> <tr valign="top"> <TD>totalk </ TD > <TD>数据表中的合计</ TD> </ TR> <tr valign="top"> <TD>I </ TD> <TD>的活动行数</ TD> </ TR > <tr valign="top"> <TD> namei </ TD> <TD>的活动行的名称</ TD> </ TR> <tr valign="top"> <TD><X > </ TD> <TD>边际的活动行</ TD> </ TR> <tr valign="top"> <TD>fi </ TD> <TD>预测活动行</ TD> </ TR> <tr valign="top"> <TD> Fs </ TD> <TD>卡方距离的活动行其平均</ TD> </ TR> <TR VALIGN =“顶”> <TD>d2i </ TD> <TD>的活动列数</ TD> </ TR> <tr valign="top"> <TD>J </ TD> <TD>活动列的名称</ TD> </ TR> <tr valign="top"> <TD>namej </ TD> <TD>边际的活动列</ TD> </ TR> <tr valign="top"> <TD>fj </ TD> <TD>预测活动列</ TD> </ TR> <tr valign="top"> <TD> X> </ TD> <TD>卡方距离的活动列，他们的平均</ TD> </ TR> <tr valign="top"> <TD>Gs </ TD> <TD >的补充行数</ TD> </ TR> <tr valign="top"> <TD> d2j </ TD> <TD>补充行的名称</ TD> </ TR> <TR VALIGN =“”> <TD>Isr </ TD> <TD>边际的补充行</ TD> </ TR> <tr valign="top"> <TD>nameisr / TD> <TD>补充行预测</ TD> </ TR> <tr valign="top"> <TD> fisr </ TD> <TD>卡方距离的补充行到平均</ TD> </ TR> <tr valign="top"> <TD>Fssr </ TD> <TD>矩阵X行补充</ TD> </ TR> <TR VALIGN =“顶“<TD>d2isr </ TD> <TD>补充列数</ TD> </ TR> <tr valign="top"> <TD> Xsr </ TD> <TD>辅助列的名称</ TD> </ TR> <tr valign="top"> <TD>Jsc </ TD> <TD>边际的补充列</ TD> </ TR> <tr valign="top"> <TD> namejsc </ TD> <TD>预测的补充列</ TD> </ TR> <tr valign="top"> <TD>fjsc </ TD> <TD>辅助列的卡方距离的平均值</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Amaya Zarraga, Beatriz Goitisolo
参考文献----------References----------
Greenacre, M. (2007). Correspondence Analysis in Practice. 2nd edition. Chapman and Hall/CRC, London.
Lebart, L; Piron, M., Morineau, A. (2006). Statistique exploratoire multidimensionnelle: visualisations et inferences en fouille de donnees. 4th edition. Dunod, Paris.
参见----------See Also----------
CorrAnGraph, CorrAnSummary
CorrAnGraph，CorrAnSummary
实例----------Examples----------
data(shoplifting)
dataCA <- shoplifting[1:13, 1:9]
### CA without supplementary elements[＃＃CA没有补充元素]
CorrAn(data=dataCA)
### CA with supplementary rows/columns[＃＃CA与补充的行/列]
CorrAn(data=dataCA, sr=13, sc=9)
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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 2012-9-30 09:35:20
