# tests/testthat/test_correlation_dim.R In nonlinearTseries: Nonlinear Time Series Analysis

```library(nonlinearTseries)
context("Correlation dimension")

test_that("estimates equal theoretical results", {
skip_on_cran()
set.seed(1)
# Henon: 1.25 +- 0.02 (Grassberger and Procaccia 1983) -----------
set.seed(1)
ts = henon(
n.sample = 5000,
n.transient = 100,
start = c(0.73954883, 0.04772637),
do.plot = FALSE
)\$x
x = corrDim(
time.series = ts,
min.embedding.dim = 2,
max.embedding.dim = 5,
time.lag = 1,
do.plot = FALSE,
theiler.window = 30,
number.boxes = 100
)
expect_equal(estimate(x), 1.25, tolerance = 2 * 10 ^ -2)

# Lorenz I: 2.05 ± 0.01 (Grassberger and Procaccia 1983) -----------
ts = lorenz(
start = c(-10, -11, 47),
time =  seq(0, 150, by = 0.01),
do.plot = FALSE
)\$x

x = corrDim(
time.series = ts,
min.embedding.dim = 4,
max.embedding.dim = 7,
time.lag = 10,
do.plot = FALSE,
theiler.window = 100,
number.boxes = 100
)
expect_equal(estimate(x), 2.05, tolerance = 1 * 10 ^ -2)

# Logistic map: 0.500 ± 0.005 (Grassberger and Procraccia 1983) -----------
ts = logisticMap(
r = 3.5699456,
n.sample = 5000,
n.transient = 500,
do.plot = FALSE
)
x = corrDim(
time.series = ts,
min.embedding.dim = 2,
max.embedding.dim = 4,
time.lag = 1,
do.plot = FALSE,
theiler.window = 100,
number.boxes = 100
)
expect_equal(0.500, estimate(x), tolerance = 5 * 10 ^ -3)

# Rossler: 1.991 + 0.065 (http://sprott.physics.wisc.edu/chaos/comchaos.htm.)
r = rossler(
a = 0.2,
b = 0.2,
w = 5.7,
start = c(1, 1, 1),
time = seq(0, 300, 0.01),
do.plot = FALSE
)
ts = r\$x
mmin = 2
mmax = 5
time.lag = 30
rmin = 0.15
rmax = 0.4
np = 20
theiler.window = 200
x = corrDim(
time.series = ts,
min.embedding.dim = mmin,
max.embedding.dim = mmax,
time.lag = time.lag,