getTarget: Construct a target matrix for single target linear shrinkage
In HGray384/TAS: Target-Averaged Linear Shrinkage (TAS)

Description Usage Arguments Value See Also Examples

View source: R/RcppExports.R

Construct a popular target matrix from the linear shrinkage literature. These targets consist of a combination of variance and correlation structure. Possible variance structures are unit, sample mean, and sample. Possible correlation structures are zero, sample mean, and autocorrelation.

1	getTarget(X, varNumber = 2L, corNumber = 1L)

`X`	`matrix` – data matrix with variables in rows and observations in columns.
`varNumber`	`numeric` – c(1, 2, 3) variance structure for the target matrix. 1 sets all variances equal to 1. 2 sets all variances equal to their sample mean (using `X`). 3. sets all variances to their sample values (using `X`).
`corNumber`	`numeric` – c(1, 2, 3) correlation structure for the target matrix. 1 sets the correlations to 0. 2 sets the correlations equal to their sample mean (using `X`). 3 sets the correlations equals to an autocorrelation structure with parameter equal to the sample mean (using `X`).

matrix – target matrix for linear shrinkage estimation.

gcShrink

  set.seed(102)
  X <- matrix(rnorm(50), 10, 5) # p=10, n=5, identity covariance
  X <- t(scale(t(X), center=TRUE, scale=FALSE)) # mean 0
  getTarget(X, varNumber = 1, corNumber = 1) # unit variance, zero correlation
  getTarget(X, varNumber = 2, corNumber = 1) # equal variance, zero correlation
  getTarget(X, varNumber = 3, corNumber = 1) # sample variances, zero correlation