Nonparametric test for intervention effect on time series count data - San Pedro, Marcus Jude P.
Abstract (Intervention effect triggers possible alteration in the behavior of the system, this is particularly highlighted in count time series data. We postulate an integer-valued autoregressive process and incorporates a temporary structural change as additive intervention effect. We propose a nonparametric test for the significance of intervention effect via the empirical distribution of test statistics through residual-based bootstrap. Simulation study shows that the nonparametric test has estimated size less than a setting of an alpha in most cases and exhibits high power especially when the intervention effect does not persist through time).