RT Journal Article
T1 A nonparametric distributionf-free test for serial independence of errors
A1 Du, Zaichao
A1 Escanciano, Juan Carlos
AB In this article, we propose a test for the serial independence of unobservable errors in location-scale models. We consider a Hoeffding-Blum-Kiefer-Rosenblat type empirical process applied to residuals, and show that under certain conditions it converges weakly to the same limit as the process based on true errors. We then consider a generalized spectral test applied to estimated residuals, and get a test that is asymptotically distribution-free and powerful against any type of pairwise dependence at all lags. Some Monte Carlo simulations validate our theoretical findings.
PB Taylor & Francis
SN 0747-4938
YR 2014
FD 2014-09-03
LK https://hdl.handle.net/10016/35043
UL https://hdl.handle.net/10016/35043
LA eng
NO Research of first author funded by Ministry of Education of China, 11XJC790002 and the National Natural Science Foundation of China, 71401140. Research of second author has been funded by the Spanish Plan Nacional de I+ D+ I, reference number SEJ2007-62908.
DS e-Archivo
RD 1 sept. 2024