mergeCoeff(MergeMaid)
mergeCoeff()所属R语言包:MergeMaid
Class mergeCoeff, a class for storing regression coefficients.
mergeCoeff类,一类用于存储回归系数。
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This is the class representation for output from regression coefficient calculations
这是回归系数计算输出类表示
插槽----------Slots----------
coeff Object of class matrix, A matrix storing default
coeff对象类的矩阵,矩阵存储默认
coeff.std Object of class matrix, A matrix storing standardized
coeff.std对象类矩阵,矩阵存储标准化
zscore Object of class matrix, A matrix storing zscores.
zscore对象类矩阵,矩阵存储zscores。
方法----------Methods----------
Class-specific methods:
类的具体方法:
coeff (mergeCoeff) Accessor function for the coeff slot.
为coeff插槽coeff(mergeCoeff)的存取功能。
coeff<- (mergeCoeff) Replacement function for the coeff slot.
coeff < - (mergeCoeff)coeff插槽更换功能。
stdcoeff (mergeCoeff) Accessor function for the coeff.std slot.
stdcoeff(mergeCoeff)为coeff.std插槽存取功能。
stdcoeff<- (mergeCoeff) Replacement function for the coeff.std slot.
<stdcoeff - (mergeCoeff)更换为coeff.std插槽功能。
zscore (mergeCoeff) Accessor function for the zscore slot.
zscore(mergeCoeff)为zscore插槽存取功能。
zscore<- (mergeCoeff) Replacement function for the zscore slot.
<zscore - (mergeCoeff)更换为zscore插槽功能。
Standard generic methods:
标准的通用方法:
plot (list) This method is not formally defined for mergeCoeff objects but for a matrix. This function would typically be called with the following syntax, plot(coeff(mergeCoeff)).The result is pairwise scatterplots of the columns of the selected matrix. If there are two studies, this is a single scatterplot.
图(名单)此方法没有正式定义为mergeCoeff对象,但矩阵。此功能通常被称为用下面的语法,图(coeff(mergeCoeff))。结果是选定矩阵列的成对散点图。如果有两项研究,这是一个单一的散点图。
参见----------See Also----------
mergeExprs,modelOutcome, mergeExpressionSet-class
mergeExprs,modelOutcome,mergeExpressionSet-class
举例----------Examples----------
if(require(Biobase) & require(MASS) & require(survival)){
data(mergeData)
merged <- mergeExprs(sample1,sample2,sample3)
log.coeff <- modelOutcome(merged,outcome=c(1,1,1),method="logistic")
plot(coeff(log.coeff))
plot(stdcoeff(log.coeff),pch=4,labels=c("study A","study B","study C"),col=3)
linear.coeff <- modelOutcome(merged[1:2],outcome=c(3,3),method="linear")
plot(zscore(linear.coeff))
plot(zscore(linear.coeff),xlab="study A",ylab="study B",col=2)
}
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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