lasso.multiSplit(lol)
lasso.multiSplit()所属R语言包:lol
Multi-split lasso
多分裂套索
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Multi-split lasso as described in Meinshausen 2009
多裂套索描述2009年在Meinshausen
用法----------Usage----------
lasso.multiSplit(y, x=NULL, lambda1=NULL, nSubsampling=200, model='linear', alpha=0.05, gamma.min=0.05, gamma.max=0.95, track=FALSE, ...)
参数----------Arguments----------
参数:y
A vector of gene expression of a probe, or a list object if x is NULL. In the latter case y should a list of two components y and x, y is a vector of expression and x is a matrix containing copy number variables
一个向量基因表达的探针,或一个列表对象,如果x是NULL。在后者情况下,y应列表两部分组成Y和X,Y是一个表达向量,并拷贝数变量,x是一个矩阵
参数:x
Either a matrix containing CN variables or NULL
无论是矩阵点数变量或NULL
参数:nSubsampling
number of splits, default to 200
数分裂,默认为200
参数:model
which model to use, one of "cox", "logistic", "linear", or "poisson". Default to 'linear'
模型使用,“考克斯”,“MF”,“线性”或“泊松”。默认为“线性”
参数:alpha
specify significant level to determine the non-zero coefficients in the range of 0 and 1, default to 0.05
指定极显着水平,确定范围,默认为0和1的非零系数为0.05
参数:gamma.min
the lower bound of gamma
下界的伽玛
参数:gamma.max
the higher bound of gamma
较高的伽玛
参数:lambda1
minimum lambda to be used, if known
最低lambda来使用,如果已知
参数:track
track progress
跟踪进度
参数:...
other parameters to be passed to lass.cv
其他参数被传递到lass.cv
Details
详情----------Details----------
This function performs the multi-split lasso as proposed by Meinshausen et al. 2009. The samples are first randomly split into two disjoint sets, one of which is used to find non-zero coefficients with a regular lasso regression, then these non-zero coefficients are fitted to another sample set with OLS. The resulting p-values after multiple runs can then be aggregated using quantiles.
执行此功能的多分裂套索作为由Meinshausen等建议。 2009年。样品首先随机分裂成两个不相交的集合,其中之一是用来寻找一个普通的套索回归非零系数,那么这些非零系数安装与母机另设样品。多次运行后产生的p值,然后可以使用位数的聚合。
值----------Value----------
A list object of class 'lol', consisting of:
一类“LOL”组成,列表中的对象:
参数:beta
coefficients
系数
参数:mat
the Q_gamma matrix as described in the paper
Q_gamma矩阵中所述的文件
参数:residuals
residuals, here is only the input y
残差,这里仅是输入y
参数:pmat
the adjusted p matrix as described in the paper
调整后的p矩阵中所述的文件
作者(S)----------Author(s)----------
Yinyin Yuan
参考文献----------References----------
P-values for high-dimensional regression. Journal of the American Statistical Association, 104, 1671-1681.
参见----------See Also----------
lasso
套索
举例----------Examples----------
data(chin07)
data <- list(y=chin07$ge[1,], x=t(chin07$cn))
res <- lasso.multiSplit(data, nSubsampling=50)
res
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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