testRmACD: LM test of no Remaining ACD (Meitz and Terasvirta, 2006)
Description
Tests if there is any remaining ACD structure in the residuals
Usage
testRmACD(fitModel, pStar = 2, robust = TRUE)
Value
a list containing:
chi2
the value of the LM statistic.
pv
the pvalue of the test statistic.
Arguments
fitModel
a fitted ACD model, i.e. an object of class "acdFit".
pStar
the number of alpha parameters in the alternative hypothesis. See \(p*\) under 'Details'.
robust
if TRUE the LM statistic will be calculated using the "robust" version, making its asymptotic behavior unaffected by possible misspecification of the error term distribution (Meitz and Terasvirta, 2006).
Author
Markus Belfrage
Details
For the model
$$x_i = \mu_i \phi_i \epsilon_i,$$
$$\mu_i = \omega + \sum_{j=1}^{p} \alpha_j x_{i-j} + \sum_{j=1}^{q} \beta_j \mu_{i-j},$$
$$\phi_i = 1 + \sum_{j=1}^{p*} \frac{x_{i-j}}{\mu_{i-j}},$$
the function tests the null hypothesis
$$H_0: \phi_i = 1.$$
References
Meitz, M. and Terasvirta, T. (2006).
Evaluating models of autoregressive conditional duration. Journal of Business and Economic Statistics 24: 104-124.