Description Usage Arguments Details Value References Examples
This function aggregates a list of selection sets by modified ADAGES.
1 | agg.ADAGES.mod(Shat.list, p)
|
Shat.list |
list of K elements containing the selection sets. |
p |
number of original variables of the model. |
The function can be used in combination with multi.knockoffs
and
multi.knockfilter
.
The function does not have to be used in the context of multiple knockoffs. It can also be used to aggregate the selection sets of any FDR controlling procedure in general.
Applies the minimization of the trade-off between the threshold and the model complexity c |S|.
A list containing following components:
Shat |
aggregated selection set. |
c |
optimal threshold. |
K |
number of aggregated sets. |
Gui (2020). ADAGES: adaptive aggregation with stability for distributed feature selection. Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference. https://arxiv.org/pdf/2007.10776.pdf
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | #Multiple knockoff example
n <- 400; p <- 200; s_0 <- 30
amplitude <- 1; mu <- rep(0,p); rho <- 0.25
Sigma <- toeplitz(rho^(0:(p-1)))
X <- MASS::mvrnorm(n, mu, Sigma)
nonzero <- sample(p, s_0)
beta <- amplitude * (1:p %in% nonzero)
y <- X %*% beta + rnorm(n)
Xk <- multi.knockoffs(X, K = 5)
multi.res <- multi.knockfilter(X, Xk, y)
agg.ADAGES.mod(multi.res$Shat.list, p = p)
#General example (selection sets with indices between 1 and 30)
Shat.list <- list(s1 = c(2,4,3,1,20,30), s2 = c(3,30,23,1,4,8),
s3=c(3,4,5,13,15,12, 23:29, 30), s4 = c(1:10, 13:15, 17),
s5 = c(15:20, 23))
agg.ADAGES.mod(Shat.list, p = 30)
|
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