tsDyn (version 0.9-44)

delta: delta test of conditional independence

Description

delta statistic of conditional independence and associated bootstrap test

Usage

delta(x, m, d = 1, eps)
delta.test(x, m = 2:3, d = 1, eps = seq(0.5 * sd(x), 2 * sd(x), length =
  4), B = 49)

Arguments

x

time series

m

vector of embedding dimensions

d

time delay

eps

vector of length scales

B

number of bootstrap replications

Value

delta returns the computed delta statistic. delta.test returns the bootstrap based 1-sided p-value.

Warning

Results are sensible to the choice of the window eps. So, try the test for a grid of m and eps values. Also, be aware of the course of dimensionality: m can't be too high for relatively small time series. See references for further details.

Details

delta statistic of conditional independence and associated bootstrap test. For details, see Manzan(2003).

References

Sebastiano Manzan, Essays in Nonlinear Economic Dynamics, Thela Thesis (2003)

See Also

BDS marginal independence test: bds.test in package tseries

Teraesvirta's neural network test for nonlinearity: terasvirta.test in package tseries

delta test for nonlinearity: delta.lin.test

Examples

# NOT RUN {
delta(log10(lynx), m=3, eps=sd(log10(lynx)))
# }