Sammanfattning
This paper introduces a suite of tests for linear and general non-
linear serial dependence. The problem is complex as the number of
variations of realistic non-linear alternatives is very large.
The alternative model is dened in terms of penalized truncated
polynomial splines, making the approximation capable of accurately
approximating a large class of linear and non-linear processes.
The asymptotic distribution for the test statistic is derived, and we
show using Monte Carlo simulations that one test is equivalent to the
Ljung-Box test, other linear tests corresponds to ordinary or partial
sample autocorrelation while the non-linear versions are capable of de-
tecting non-linear eects, even when other tests fail to do so.
linear serial dependence. The problem is complex as the number of
variations of realistic non-linear alternatives is very large.
The alternative model is dened in terms of penalized truncated
polynomial splines, making the approximation capable of accurately
approximating a large class of linear and non-linear processes.
The asymptotic distribution for the test statistic is derived, and we
show using Monte Carlo simulations that one test is equivalent to the
Ljung-Box test, other linear tests corresponds to ordinary or partial
sample autocorrelation while the non-linear versions are capable of de-
tecting non-linear eects, even when other tests fail to do so.
Originalspråk | engelska |
---|---|
Sidor (från-till) | 551-566 |
Tidskrift | Applied Mathematical Sciences |
Volym | 7 |
Nummer | 12 |
Status | Published - 2013 |
Ämnesklassifikation (UKÄ)
- Sannolikhetsteori och statistik