In this paper two tests of serial independence are proposed. The building block of these procedures is the definition of a component chi-square test for testing independence between pairs of lagged variables. With reference to different component chi-square tests, it is shown that the corresponding test statistics are independent. Taking advantage of this result, the component tests are used from both a simultaneous and a direct viewpoint to define two different test procedures denoted by SIS (Serial Independence Simultaneous) and SICS (Serial Independence Chi-Square). Simulations are used to explore the performance of these tests in terms of size and power. Our results underline that both the proposals are powerful against various types of alternatives. It is also shown, through what we call Lag Subsets Dependence Plot (LSDP), how to detect possible lag(s)-dependences graphically. Some examples are finally provided in order to evaluate the effectiveness of the LSDP.
|Numero di pagine||18|
|Rivista||STATISTICA & APPLICAZIONI|
|Stato di pubblicazione||Pubblicato - 2010|
- Chi-square test
- Nonlinear time series
- Serial independence