testRmACD: LM test of no Remaining ACD (Meitz and Terasvirta, 2006)

In ACDm: Tools for Autoregressive Conditional Duration Models

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)

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).

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.

Value

a list containing:

chi2	the value of the LM statistic.
pv	the pvalue of the test statistic.

Author(s)

Markus Belfrage

References

Meitz, M. and Terasvirta, T. (2006). Evaluating models of autoregressive conditional duration. Journal of Business and Economic Statistics 24: 104-124.

See Also

testTVACD, testSTACD.

Examples

fitModel3000obs <- acdFit(adjDurData[1:3000,])
testRmACD(fitModel3000obs, pStar = 2, robust = TRUE)

ACDm documentation built on May 29, 2024, 12:04 p.m.