print.FRESHD {FRESHD} | R Documentation |
Print Function for objects of Class FRESHD
Description
This function will print some information about the FRESHD object.
Usage
## S3 method for class 'FRESHD'
print(x, ...)
Arguments
x |
a FRESHD object |
... |
ignored |
Details
A three-column data.frame with columns 'sparsity', 'Df' and 'lambda'. The 'Df' column is the number of nonzero coefficients and 'sparsity' is the percentage of zeros in the solution.
Value
The data.frame above is silently returned
Author(s)
Adam Lund
Examples
##size of example
set.seed(42)
G <- 50; n <- c(65, 26, 13); p <- c(13, 5, 4)
sigma <-0.1
nlambda =30
##marginal design matrices (Kronecker components)
x <- list()
for(i in 1:length(n)){x[[i]] <- matrix(rnorm(n[i] * p[i],0,sigma), n[i], p[i])}
##common features and effects
common_features <- rbinom(prod(p), 1, 0.1)
common_effects <- rnorm(prod(p), 0, 0.1) * common_features
##group response and fit
lambda <- exp(seq(0, -5, length.out = nlambda))
B <- array(NA, c(prod(p), nlambda, G))
y <- array(NA, c(n, G))
for(g in 1:G){
bg <- rnorm(prod(p), 0, 0.1) * (1 - common_features) + common_effects
Bg <- array(bg, p)
mu <- RH(x[[3]], RH(x[[2]], RH(x[[1]], Bg)))
y[,,, g] <- array(rnorm(prod(n), 0, var(mu)), dim = n) + mu
}
##fit model for range of lambda
system.time(fit <- maximin(y, x, penalty = "lasso", alg = "tos"))
Betahat <- fit$coef
##estimated common effects for specific lambda
modelno <- 20;
m <- min(Betahat[, modelno], common_effects)
M <- max(Betahat[, modelno], common_effects)
plot(common_effects, type = "h", ylim = c(m, M), col = "red")
lines(Betahat[, modelno], type = "h")
[Package FRESHD version 1.0 Index]