| invvar {ruv} | R Documentation |
Inverse Method Variances
Description
Estimate the features' variances using the inverse method. This function is usually called from RUVinv and not normally intended for stand-alone use.
Usage
invvar(Y, ctl, XZ = NULL, eta = NULL, lambda = NULL,
invsvd = NULL)
Arguments
Y |
The data. A m by n matrix, where m is the number of samples and n is the number of features. |
ctl |
The negative controls. A logical vector of length n. |
XZ |
A m by (p + q) matrix containing both the factor(s) of interest (X) and known covariates (Z). |
eta |
Gene-wise (as opposed to sample-wise) covariates. These covariates are adjusted for by RUV-1 before any further analysis proceeds. A matrix with n columns. |
lambda |
Ridge parameter. If specified, the ridged inverse method will be used. |
invsvd |
Can be included to speed up execution. Generally used when calling invvar many times with different values of lambda. |
Value
A list containing
sigma2 |
Estimates of the features' variances. A vector of length n. |
df |
The "effective degrees of freedom" |
invsvd |
Can be used to speed up future calls of invvar. |
Author(s)
Johann Gagnon-Bartsch johanngb@umich.edu
References
Removing Unwanted Variation from High Dimensional Data with Negative Controls. Gagnon-Bartsch, Jacob, and Speed, 2013. Available at: http://statistics.berkeley.edu/tech-reports/820.