Nothing
context("test_susie_trendfilter.R")
#check if the susie_trendfilter produces the same results as the original version
test_that("susie for trend filtering",{
#order 0 trend filtering
with(simulate_tf(0), {
original.s0 = susie(X,y,estimate_prior_variance = FALSE)
s0 = susie_trendfilter(y,0,estimate_prior_variance = FALSE, standardize = TRUE, use_mad=FALSE)
original.s0.ns.ni = susie(X,y,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE)
s0.ns.ni = susie_trendfilter(y,0,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE)
original.s0.ns = susie(X,y,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE)
s0.ns = susie_trendfilter(y,0,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE, use_mad=FALSE)
original.s0.ni = susie(X,y,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE)
s0.ni = susie_trendfilter(y,0,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE)
expect_equal_susie(s0, original.s0)
expect_equal_susie(s0.ns.ni, original.s0.ns.ni)
expect_equal_susie(s0.ns, original.s0.ns)
expect_equal_susie(s0.ni, original.s0.ni)
})
#order 1 trend filtering
with(simulate_tf(1), {
suppressWarnings({
original.s1 <- susie(X,y,estimate_prior_variance = FALSE)
s1 <- suppressWarnings(susie_trendfilter(y,1,estimate_prior_variance = FALSE, standardize = TRUE, use_mad=FALSE))
original.s1.ns.ni <- susie(X,y,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE)
s1.ns.ni <- suppressWarnings(susie_trendfilter(y,1,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE))
original.s1.ns <- susie(X,y,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE)
s1.ns <- suppressWarnings(susie_trendfilter(y,1,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE, use_mad=FALSE))
original.s1.ni <- susie(X,y,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE)
s1.ni <- suppressWarnings(susie_trendfilter(y,1,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE))
})
expect_equal_susie(s1, original.s1)
expect_equal_susie(s1.ns.ni, original.s1.ns.ni)
expect_equal_susie(s1.ns, original.s1.ns)
expect_equal_susie(s1.ni, original.s1.ni)
})
#order 2 trend filtering
with(simulate_tf(2), {
original.s2 = susie(X,y,estimate_prior_variance = FALSE)
s2 = suppressWarnings(susie_trendfilter(y,2,estimate_prior_variance = FALSE, standardize = TRUE, use_mad=FALSE))
original.s2.ns.ni = susie(X,y,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE)
s2.ns.ni = suppressWarnings(susie_trendfilter(y,2,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE))
original.s2.ns = susie(X,y,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE)
s2.ns = suppressWarnings(susie_trendfilter(y,2,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE, use_mad=FALSE))
original.s2.ni = susie(X,y,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE)
s2.ni = suppressWarnings(susie_trendfilter(y,2,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE))
expect_equal_susie(s2, original.s2)
expect_equal_susie(s2.ns.ni, original.s2.ns.ni)
expect_equal_susie(s2.ns, original.s2.ns)
expect_equal_susie(s2.ni, original.s2.ni)
})
})
#check if susie_trendfilter can fit different arguments
test_that("susie_trendfilter interface",{
with(simulate_tf(0), {
n = length(y)
expect_error(susie_trendfilter(y,0,standardize = TRUE, estimate_prior_variance=TRUE, use_mad=FALSE), NA)
expect_error(susie_trendfilter(y,0,standardize = TRUE, null_weight=1/(n+1),estimate_prior_variance = FALSE, use_mad=FALSE), NA)
expect_error(susie_trendfilter(y,0,standardize = TRUE, estimate_prior_variance=TRUE, null_weight=1/(n+1), use_mad=FALSE), NA)
expect_error(susie_trendfilter(y,0,standardize=FALSE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE), NA)
expect_error(susie_trendfilter(y,0,standardize=FALSE,intercept=TRUE,estimate_prior_variance = FALSE, use_mad=FALSE), NA)
expect_error(susie_trendfilter(y,0,standardize=TRUE,intercept=FALSE,estimate_prior_variance = FALSE, use_mad=FALSE), NA)
expect_error(suppressWarnings(susie_trendfilter(y,0,standardize = TRUE, compute_univariate_zscore =TRUE,estimate_prior_variance = FALSE, use_mad=FALSE)), NA)
})
})
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