print.FRESHD: Print Function for objects of Class FRESHD

In FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data

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")

FRESHD documentation built on May 12, 2022, 9:06 a.m.