sempls(semPLS)
sempls()所属R语言包：semPLS
Structural Equation Modeling by Partial Least Squares
偏最小二乘法的结构方程模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
sempls fits structural equation models by the patial least squares (PLS) method. The estimation is based on the raw data and requires no distributional assumptions.
sempls符合结构方程模型（ε2）最小二乘（PLS）方法。的估计是基于原始数据和不需要分布式的假设。
用法----------Usage----------
sempls(model, ...)
## S3 method for class 'plsm'
sempls(model, data, maxit=20, tol=1e-7,
scaled=TRUE, sum1=FALSE, wscheme="centroid", pairwise=FALSE,
method=c("pearson", "kendall", "spearman"),
convCrit=c("relative", "square"),
verbose=TRUE, ...)
## S3 method for class 'sempls'
print(x, digits=2, ...)
## S3 method for class 'sempls'
plot(x, ...)
## S3 method for class 'sempls'
densityplot(x, data, use=c("fscores", "prediction",
"residuals"), ...)
pathCoeff(object, ...)
## S3 method for class 'sempls'
pathCoeff(object, ...)
## S3 method for class 'pathCoeff'
print(x, na.print=".", digits=2, abbreviate=FALSE, ...)
totalEffects(object)
## S3 method for class 'sempls'
totalEffects(object)
## S3 method for class 'totalEffects'
print(x, na.print=".", digits=2, abbreviate=FALSE,...)
plsWeights(object)
## S3 method for class 'sempls'
plsWeights(object)
## S3 method for class 'plsWeights'
print(x, na.print=".", digits=2, abbreviate=FALSE, ...)
plsLoadings(object)
## S3 method for class 'sempls'
plsLoadings(object)
## S3 method for class 'plsLoadings'
print(x, type=c("discriminant", "outer", "cross"),
cutoff=NULL, reldiff=0.2, na.print=".", digits=2, abbreviate=FALSE, ...)
参数----------Arguments----------
参数：model
An object inheriting from class plsm as returned from plsm or read.splsm.
一个继承类的对象plsm返回plsm或read.splsm。
参数：...
Arguments to be passed down.
要传递了下来。
参数：data
A data.frame containing the observed variables (MVs). The storage mode for all the MVs included in the model must be numeric.
Adata.frame观测变量（MVS）。的存储模式必须包含在模型中所有的MVnumeric。
参数：maxit
A numeric value, which determines the maximum number of iterations performed by the PLS algorithm. The default is 20 iterations.
Anumeric值，它决定了最大数量的PLS算法执行的迭代。默认值是20迭代。
参数：tol
A numeric value, specifying the tolerance for the maximum relative differences in the outer weights. The default value is 10^{-7}.
Anumeric值，指定外的权重最大相对差异的容忍。默认值是10^{-7}。
参数：scaled
A logical value indicating, whether the observed data shall be scaled to zero mean and unit variance. The default is TRUE.
Alogical值，该值指示是否应扩展到零均值和单位方差的观测数据。默认的TRUE。
参数：sum1
A logical value indicating, whether the outer weights foreach latent variable (LV) shall be standardized to sum up to one. The default is FALSE. Since the factor scores are scaled in each step of the PLS algorithm, changing this value to TRUE does not affect the results.
Alogical值，该值指示是否外权重的foreach潜变量（LV）应是标准化的一个总结。默认的FALSE。由于各因子得分按比例PLS算法的每一步，改变这个值TRUE不影响结果。
参数：wscheme
A character naming the weighting scheme to use. Possible values are:
Acharacter命名权重方案使用。可能的值有：
"A" or "centroid" for the centroid scheme, the default,
"A"或"centroid"质心的计划，在默认情况下，
"B" or "factorial"for the factorial scheme and
"B"或"factorial"的阶乘计划和
"C", "pw" or "pathWeighting" for the path weighting scheme.
"C"，"pw"或"pathWeighting"的路径的权重方案。
参数：pairwise
A logical value indicating, whether correlations shall be calculated pairwise. If the observed data does not contain missing values, the results are not affected. The default is FALSE. For more details the R help, ?cor, can be consulted.
Alogical值，该值指示是否计算应两两相关性。如果所观察到的数据中不包含缺失值，结果不会受到影响。默认的FALSE。欲了解更多详情的R帮助，?cor，可以咨询。
参数：method
A character naming the method to calculate the correlations. Possible values are:
Acharacter命名的方法来计算的相关性。可能的值有：
"pearson" , the default,
"pearson"，默认情况下，
"kendall",
"kendall"，
"spearman".
"spearman"。
For more details on the method, the R help, ?cor, can be consulted. Note, that despite of the method argument, pearson correlations are always used for the inner approximation (step 2).
欲了解更多详细信息的方法，在R帮助，?cor，可以咨询。请注意，尽管method参数，皮尔森相关性总是用于内近似（步骤2）。
参数：convCrit
The convergence criteria to use:
的收敛标准使用方法：
"relative", the default,
"relative"，默认情况下，
"square".
"square"。
参数：verbose
Logical: If FALSE no status messages are printed.
逻辑：如果FALSE没有状态消息被打印出来。
参数：object
An object of class sempls.
对象的类sempls。
参数：x
An object of the according class.
根据类的一个目的。
参数：type
If the argument what="loadings", type describes the loadings to be extracted – those are:
如果该参数what="loadings"，type说明要提取的负荷 - 这些是：
"discriminant", the default, contrasts outer against cross loadings to check for discrimant validity of the measurement model,
"discriminant"，默认情况下，对比外对交叉负载量的检查discrimant测量模型的有效性，
"outer" for the outer loadings and
"outer"的外载荷和
"cross" for the cross loadings.
"cross"的交叉负荷。
参数：cutoff
A numerical value at which to cutoff the loadings – this means loadings smaller than the cutoff value will not be printed.
一个数值，在截止负荷 - 这意味着负荷小于临界值不会被打印出来。
参数：reldiff
The argument is only effectiv when type="discriminant". It is a numeric value, specifying the relative difference between outer and cross loadings at which cross loadings will still be printed.
的说法是唯一有效作者type="discriminant"。它是一个numeric的值，指定仍将被打印在该交叉负荷之间的相对差的外表面和横载荷。
参数：na.print
A character substituting values not to be printed.
Acharacter值替换不被打印出来。
参数：digits
minimal number of _significant_ digits, see print.default.
数量最少的_significant_数字，请参阅print.default。
参数：use
The values for which the density plots are created. If
值的密度图。如果
"fscores": the factor scores are used,
"fscores"：各因子得分，
"prediction": the estimated factor scores are used,
"prediction"：估计因子得分，
"residuals": the residuals are used.
"residuals"：使用的残差。
参数：abbreviate
A logical indicating whether dimnames should be abbreviated. For Details see abbreviate. The default is FALSE.
一个逻辑指示是否dimnames应该是缩写。如需详细资讯，请参阅：abbreviate。默认的FALSE。
值----------Value----------
sempls returns an object of class sempls, with the following elements:
sempls返回一个对象类sempls，包含下列元素：
参数：coefficients
A data.frame containing the estimates for all the arcs in the path model, those are the outer loadings for mode "A" type LVs and outer weights for mode "B" type LVs and path coefficients for those belonging to the structural model.
Adata.frame包含路径模型中的所有弧的估计，这些是那些属于模式A型的LV和外模式B型LV和路径系数权重的外载荷结构模型。
参数：path_coefficient
The matrix of path coefficients.
matrix的路径系数。
参数：outer_loadings
The matrix of outer loadings.
matrix的外荷载。
参数：cross_loadings
The matrix of cross loadings.
matrix的交叉负载量。
参数：total_effects
The matrix of total effects.
matrix的总效果。
参数：inner_weights
The matrix of inner weights.
matrix内的权重。
参数：outer_weights
The matrix of outer weights.
matrix外的权重。
参数：factor_scores
A data.frame containing the estimated factor scores for the LVs.
Adata.frame估计因子得分的LV。
参数：data
A data.frame containing the preprocessed obseravtions of the MVs.
Adata.frame包含预处理obseravtions的MV。
参数：incomplete
The index of the incomplete observations.
不完整的观测的索引。
参数：...
All the other values are just storing information used in the call.
所有其他值都存储在call使用的信息。
（作者）----------Author(s)----------
Armin Monecke <a href="mailto:armin.monecke@stat.uni-muenchen.de">armin.monecke@stat.uni-muenchen.de</a>
参考文献----------References----------
Modeling Using Partial Least Squares. Journal of Statistical Software, 48(3), 1-32., URL http://jstatsoft.org/v48/i03/.
参见----------See Also----------
plsm, read.splsm, rSquared, pathDiagram, bootsempls, plsm2sem, sem
plsm，read.splsm，rSquared，pathDiagram，bootsempls，plsm2sem，sem
实例----------Examples----------
data(ECSImobi)
ecsi <- sempls(model=ECSImobi, data=mobi, wscheme="pathWeighting")
ecsi
## create plots[＃创建图]
densityplot(ecsi)
densityplot(ecsi, use="prediction")
densityplot(ecsi, use="residuals")
## Values of 'sempls' objects[值“sempls的对象]
names(ecsi)
ecsi$outer_weights
ecsi$outer_loadings
ecsi$path_coefficients
ecsi$total_effects
### using convenience methods to sempls results[＃＃用方便的方法来sempls结果]
## path coefficients[＃路径系数]
pathCoeff(ecsi)
## total effects[＃总的影响]
totalEffects(ecsi)
## get loadings and check for discriminant validity[＃负荷和判别有效性检查]
(l <- plsLoadings(ecsi))
# outer loadings[外载荷]
print(l, type="outer", digits=2)
# outer loadings greater than 0.5[外载荷大于0.5]
print(l,type="outer", cutoff=0.5, digits=2)
# cross loadings greater than 0.5[交叉负荷大于0.5]
print(ecsi, type="cross", cutoff=0.5, digits=2)
### R-squared[＃＃R-平方]
rSquared(ecsi)
### Create .dot representation of the path diagram and[＃＃创建点表示的路径图]
### create .pdf file if graphviz is available.[＃＃创建PDF格式的文件，如果graphviz的是可用的。]
## Not run: [＃不运行：]
pathDiagram(ecsi, file="ecsiPLS1", edge.labels="both",
output.type="graphics", digits=3, graphics.fmt = "pdf")
# include R-squared values[包括R-平方值]
pathDiagram(ecsi, file="ecsiPLS2", edge.labels="both",
output.type="graphics", digits=3, graphics.fmt = "pdf",
rSquared=rSquared(ecsi))
# only the structural model[只有结构模型]
pathDiagram(ecsi, file="ecsiPLS3", edge.labels="both",
output.type="graphics", digits=3, graphics.fmt = "pdf",
rSquared=rSquared(ecsi), full=FALSE)
## End(Not run)[＃（不执行）]
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。
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发表于 2012-9-30 00:43:50
