TY - JOUR
T1 - Empirical likelihood confidence intervals for the mean of a long-range dependent process
AU - Nordman, Daniel J.
AU - Sibbertsen, Philipp
AU - Lahiri, Soumendra N.
PY - 2007/7
Y1 - 2007/7
N2 - This paper considers blockwise empirical likelihood for real-valued linear time processes which may exhibit either short- or long-range dependence. Empirical likelihood approaches intended for weakly dependent time series can fail in the presence of strong dependence. However, a modified blockwise method is proposed for confidence interval estimation of the process mean, which is valid for various dependence structures including long-range dependence. The finite-sample performance of the method is evaluated through a simulation study and compared with other confidence interval procedures involving subsampling or normal approximations.
AB - This paper considers blockwise empirical likelihood for real-valued linear time processes which may exhibit either short- or long-range dependence. Empirical likelihood approaches intended for weakly dependent time series can fail in the presence of strong dependence. However, a modified blockwise method is proposed for confidence interval estimation of the process mean, which is valid for various dependence structures including long-range dependence. The finite-sample performance of the method is evaluated through a simulation study and compared with other confidence interval procedures involving subsampling or normal approximations.
KW - Blocking
KW - Confidence interval
KW - Empirical likelihood
KW - FARIMA
KW - Long-range dependence
UR - https://www.scopus.com/pages/publications/34250635445
U2 - 10.1111/j.1467-9892.2006.00526.x
DO - 10.1111/j.1467-9892.2006.00526.x
M3 - Article
AN - SCOPUS:34250635445
SN - 0143-9782
VL - 28
SP - 576
EP - 599
JO - Journal of Time Series Analysis
JF - Journal of Time Series Analysis
IS - 4
ER -