TY - JOUR
T1 - The empirical likelihood goodness-of-fit test for regression model
AU - ZHU, Lixing
AU - Qin, Yong Song
AU - Xu, Wang Li
N1 - Funding Information:
Received December 12, 2005; accepted November 2, 2006 DOI: 10.1007/s11425-007-0044-1 † Corresponding author This work was supported by the Research Grants Council Science Foundation of China (Grant No. 10661003)
PY - 2007/6
Y1 - 2007/6
N2 - Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.
AB - Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.
KW - AR time series models
KW - Asymptotic normality
KW - Empirical likelihood
KW - Goodness-of-fit
KW - Regression model
UR - http://www.scopus.com/inward/record.url?scp=34347219431&partnerID=8YFLogxK
U2 - 10.1007/s11425-007-0044-1
DO - 10.1007/s11425-007-0044-1
M3 - Article
AN - SCOPUS:34347219431
SN - 1006-9283
VL - 50
SP - 829
EP - 840
JO - Science in China, Series A: Mathematics, Physics, Astronomy
JF - Science in China, Series A: Mathematics, Physics, Astronomy
IS - 6
ER -