FRESHD (version 1.0)

print.FRESHD: Print Function for objects of Class FRESHD

Description

This function will print some information about the FRESHD object.

Usage

# S3 method for FRESHD
print(x, ...)

Arguments

x

a FRESHD object

...

ignored

Value

The data.frame above is silently returned

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.

Examples

# NOT RUN {
##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")

# }