select_p: Data-driven selection of p for the test of randomness

In MixedIndTests: Tests of Randomness and Tests of Independence

Data-driven selection of p for the test of randomness

Description

This function uses a AIC/BIC type criterion to select p based on the data.

Usage

select_p(X, p0 = 2, d = 5, q = 2.4, lambda = 0.25)

Arguments

X	Time series
p0	Minimum value of p (default is 2)
d	Maximum value of p (default is 5)
q	Constant for selecting between AIC and BIC type penalty (default is 2.4)
lambda	Penalty term (default is 0.25); small values lead to p=d, large value lead to p=p0

Value

p	Selected value of p

References

B.R Nasri (2021). Tests of serial dependence for arbitrary distributions

Examples

X <- SimAR1Poisson(c(5,0.2),100)
out <- select_p(X)

MixedIndTests documentation built on May 29, 2024, 12:19 p.m.