Nothing

```
library(nonlinearTseries)
context("ACF-based time-lag estimation")
test_that("the time lag for the Takens' vectors are properly estimated", {
skip_on_cran()
set.seed(1)
Ts = 0.01
time = seq(0, 100, Ts)
time.series = cos(2 * pi * 1 * time)
tl = timeLag(
time.series,
technique = "acf",
selection.method = "first.zero",
value = 0,
lag.max = NULL,
do.plot = FALSE
)
expect_equal(25, tl)
time.series = exp(-time)
tl = timeLag(
time.series,
technique = "acf",
selection.method = "first.e.decay",
value = 0,
lag.max = 120,
do.plot = FALSE
)
expect_equal(100, tl)
time.series = arima.sim(n = 5000, model = list(ar = 0.9, -0.9))
tl = timeLag(
time.series,
technique = "ami",
n.partitions = NULL,
selection.method = "first.e.decay",
value = 0,
lag.max = 120,
do.plot = FALSE
)
expect_equal(1, tl)
time.series = time
tl = timeLag(
time.series,
technique = "acf",
selection.method = "first.minimum",
value = 0,
lag.max = 8000,
do.plot = FALSE
)
expect_equal(7072, tl)
tl = timeLag(
time.series,
technique = "ami",
n.partitions = NULL,
selection.method = "first.minimum",
value = 0,
lag.max = 400,
do.plot = FALSE
)
expect_equal(246, tl)
tl = timeLag(
time.series,
technique = "acf",
selection.method = "first.value",
value = 0.8,
lag.max = 8000,
do.plot = FALSE
)
expect_equal(669, tl)
tl = timeLag(
time.series,
technique = "ami",
n.partitions = NULL,
selection.method = "first.value",
value = 2.5,
lag.max = 400,
do.plot = FALSE
)
expect_equal(120, tl)
})
test_that("exceptions are properly generated", {
time.series = seq(0, 100, 0.01)
# function does not cross 0.8
expect_error(
timeLag(
time.series,
technique = "acf",
selection.method = "first.value",
value = 0.8,
lag.max = 10,
do.plot = FALSE
)
)
# function does not have a minimum
expect_error(
timeLag(
time.series,
technique = "acf",
selection.method = "first.minimum",
lag.max = 10,
do.plot = FALSE
)
)
})
```

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