context("cvTool - one replication")
## load packages
library("cvTools", quietly=TRUE)
## set seed for reproducibility
set.seed(1234)
## generate data for tests
n <- 20
x <- rnorm(n)
y <- x + rnorm(n)
x <- as.matrix(x)
xy <- data.frame(x, y)
## set up function call to lm() and lts()
lmCall <- call("lm", y~x)
ltsCall <- call("ltsReg", alpha=0.75)
## set up cross-validation folds
K <- 5
R <- 1
folds <- cvFolds(n, K, R)
## run tests
test_that("matrix of results has correct dimensions", {
## LS fit
lmCV <- cvTool(lmCall, data=xy, y=xy$y, cost=rmspe, folds=folds)
expect_is(lmCV, "matrix")
expect_equal(dim(lmCV), c(R, 1))
## reweighted and raw LTS fits
ltsCV <- cvTool(ltsCall, x=x, y=y, cost=rtmspe, folds=folds,
predictArgs=list(fit="both"))
expect_is(ltsCV, "matrix")
expect_equal(dim(ltsCV), c(R, 2))
})
test_that("including standard error gives list of two numeric vectors", {
## LS fit
lmCV <- cvTool(lmCall, data=xy, y=xy$y, cost=rmspe, folds=folds,
costArgs=list(includeSE=TRUE))
expect_is(lmCV, "list")
expect_equal(length(lmCV), 2)
lmRMSPE <- lmCV[[1]]
expect_is(lmRMSPE, "numeric")
expect_equal(length(lmRMSPE), 1)
lmSE <- lmCV[[2]]
expect_is(lmSE, "numeric")
expect_equal(length(lmSE), 1)
## reweighted and raw LTS fits
ltsCV <- cvTool(ltsCall, x=x, y=y, cost=rtmspe, folds=folds,
predictArgs=list(fit="both"), costArgs=list(includeSE=TRUE))
expect_is(ltsCV, "list")
expect_equal(length(ltsCV), 2)
ltsRTMSPE <- ltsCV[[1]]
expect_is(ltsRTMSPE, "numeric")
expect_equal(length(ltsRTMSPE), 2)
ltsSE <- ltsCV[[2]]
expect_is(ltsSE, "numeric")
expect_equal(length(ltsSE), 2)
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.