loadings(stats)
loadings()所属R语言包:stats
Print Loadings in Factor Analysis
打印载荷因子分析
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Extract or print loadings in factor analysis (or principal components analysis).
提取或打印负荷因子分析(主成分分析)。
用法----------Usage----------
loadings(x)
## S3 method for class 'loadings'
print(x, digits = 3, cutoff = 0.1, sort = FALSE, ...)
## S3 method for class 'factanal'
print(x, digits = 3, ...)
参数----------Arguments----------
参数:x
an object of class "factanal" or "princomp" or the loadings component of such an object.
一个类的对象"factanal"或"princomp"或loadings这样一个对象的组件。
参数:digits
number of decimal places to use in printing uniquenesses and loadings.
数小数使用印刷的独特性和负荷。
参数:cutoff
loadings smaller than this (in absolute value) are suppressed.
负荷比这个更小(绝对值)被抑制。
参数:sort
logical. If true, the variables are sorted by their importance on each factor. Each variable with any loading larger than 0.5 (in modulus) is assigned to the factor with the largest loading, and the variables are printed in the order of the factor they are assigned to, then those unassigned.
逻辑。如果情况属实,他们对每个因素的重要性排序变量。每个变量与任何大于0.5加载(模数)被分配的最大负荷因子,变量被印在他们被分配到,那么这些未分配的因素顺序。
参数:...
further arguments for other methods.
其他方法的进一步论据。
Details
详情----------Details----------
"Loadings" is a term from factor analysis, but because factor analysis and principal component analysis (PCA) are often conflated in the social science literature, it was used for PCA by SPSS and hence by princomp in S-PLUS to help SPSS users.
荷载是一个长期性因素分析,但由于因子分析和主成分分析(PCA)在社会科学文献往往混为一谈,它被用于PCA用SPSS,因此princomp,S-PLUS帮助SPSS用户。
Small loadings are conventionally not printed (replaced by spaces), to draw the eye to the pattern of the larger loadings.
小负荷的传统不能打印(用空格代替),吸引眼球,以较大的负荷模式。
The print method for class "factanal" calls the "loadings" method to print the loadings, and so passes down arguments such as cutoff and sort.
print类的方法"factanal"调用"loadings"方法来打印负荷,所以传递下来的参数,如cutoff和sort。
参见----------See Also----------
factanal, princomp
factanal,princomp
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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