Nothing
context("Consistency of the Elastic-net solution path (package 'elasticnet')")
test_that("enet_quad2elasticnet", {
require(elasticnet)
get.enet <- function(x,y,intercept,normalize=TRUE,naive=FALSE) {
lambda2 <- runif(1,0,10)
enet.larsen <- enet(x,y,lambda=lambda2,intercept=intercept,normalize=normalize)
iols <- length(enet.larsen$penalty)
lambda1 <- enet.larsen$penalty[-iols]/2
enet.quadru <- elastic.net(x,y,intercept=intercept,normalize=normalize,
lambda1=lambda1, lambda2=lambda2, naive=naive)
quad <- list(coef = as.matrix(enet.quadru@coefficients),
meanx = enet.quadru@meanx,
normx = enet.quadru@normx)
enet <- list(coef = predict(enet.larsen, type="coefficients",naive=naive)$coefficients[-iols,],
meanx = enet.larsen$meanx,
normx = enet.larsen$normx)
return(list(quad=quad, enet = enet))
}
## PROSTATE DATA SET
load("prostate.rda")
x <- as.matrix(x)
## Run the tests...
with.intercept <-get.enet(x,y,intercept=TRUE,naive=TRUE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <- get.enet(x,y,intercept=FALSE,naive=TRUE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <- get.enet(x,y,intercept=TRUE,naive=FALSE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,naive=FALSE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <-get.enet(x,y,intercept=TRUE,normalize=FALSE,naive=TRUE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,normalize=FALSE,naive=TRUE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <-get.enet(x,y,intercept=TRUE,normalize=FALSE,naive=FALSE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,normalize=FALSE,naive=FALSE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
## RANDOM DATA
seed <- sample(1:10000,1)
## cat(" #seed=",seed)
set.seed(seed)
beta <- rep(c(0,1,0,-1,0), c(25,10,25,10,25))
n <- 100
p <- length(beta)
mu <- 3 # intercept
sigma <- 30 # huge noise
Sigma <- matrix(0.95,p,p) # huge correlation
diag(Sigma) <- 1
x <- as.matrix(matrix(rnorm(95*n),n,95) %*% chol(Sigma))
y <- 10 + x %*% beta + rnorm(n,0,10)
## Run the tests...
with.intercept <-get.enet(x,y,intercept=TRUE,naive=TRUE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,naive=TRUE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <-get.enet(x,y,intercept=TRUE,naive=FALSE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,naive=FALSE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <-get.enet(x,y,intercept=TRUE,normalize=FALSE,naive=TRUE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,normalize=FALSE,naive=TRUE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
with.intercept <-get.enet(x,y,intercept=TRUE,normalize=FALSE,naive=FALSE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE,normalize=FALSE,naive=FALSE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
## Run the tests...
with.intercept <-get.enet(x,y,intercept=TRUE)
expect_that(with.intercept$quad,
is_equivalent_to(with.intercept$enet))
without.intercept <-get.enet(x,y,intercept=FALSE)
expect_that(without.intercept$quad,
is_equivalent_to(without.intercept$enet))
})
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