add.test: Lagrange multiplier test for additivity in a timeseries

In nlts: Nonlinear Time Series Analysis

Description

add.test is a function to test the permissibility of the additive autoregressive model:

Usage

add.test(x, order, n.cond = FALSE)

Arguments

x	A time series (vector without missing values).
order	a scalar representing the order to be considered.
n.cond	The number of observation to condition on. The default is order (must be >= order)

Details

N(t) = f1(N(t-1)) + f2(N(t-2)) + ... + fd(N(t-d)) + e(t )

against the alternative:

N(t) = F(N(t-1), N(t-2), ..., N(t-d)) + e(t)

This is the Lagrange multiplier test for additivity developed by Chen et al. (1995: test II).

Value

a vector is returned consisting of the asymtpotic chi-square value, the associated d.f. and asymptotic p.val for the test of additivity.

References

Chen, R., Liu, J.S. & Tsay, R.S. (1995) Additivity tests for nonlinear autoregression. Biometrika, 82, 369-383. https://doi.org/10.1093/biomet/82.2.369

Bjornstad, O.N., Begon, M., Stenseth, N.C., Falck, W., Sait, S.M., & Thompson, D.J. (1998) Population dynamics of the Indian meal moth: demographic stochasticity and delayed regulatory mechanisms. Journal of Animal Ecology, 67, 110-126. https://doi.org/10.1046/j.1365-2656.1998.00168.x

Examples

     data(plodia)
     add.test(sqrt(plodia), order = 3)

nlts documentation built on May 1, 2019, 8:44 p.m.