# SR

From SILM v1.0.0
by Xianyang Zhang

##### Support Recovery Procedure

This function implements the support recovery procedure in Zhang and Cheng (2017).

##### Usage

`SR(X, Y)`

##### Arguments

- X
n times p design matrix.

- Y
Response variable.

##### Value

The sets of active variables selected by the support recovery procedure and the scaled Lasso.

##### References

Zhang, X., and Cheng, G. (2017) Simultaneous Inference for High-dimensional
Linear Models, *Journal of the American Statistical Association*, 112, 757-768.

##### Examples

```
# NOT RUN {
## The function is intended for large n and p.
## Use small p here for illustration purpose only.
n <- 100
p <- 10
s0 <- 7
set <- 1:s0
Sigma <- matrix(NA, p, p)
for (i in 1:p) Sigma[i,] <- 0.9^(abs(i-(1:p)))
X <- matrix(rnorm(n*p), n, p)
X <- t(t(chol(Sigma))%*%t(X))
beta <- rep(0,p)
beta[1:s0] <- runif(s0,1,2)
Y <- X%*%beta+rt(n,4)/sqrt(2)
SR(X, Y)
# }
```

*Documentation reproduced from package SILM, version 1.0.0, License: GPL-3*

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