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Empirical likelihood confidence intervals for the mean of a long‐range dependent process
Author(s) -
Nordman Daniel J.,
Sibbertsen Philipp,
Lahiri Soumendra N.
Publication year - 2007
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2006.00526.x
Subject(s) - mathematics , range (aeronautics) , confidence interval , empirical likelihood , statistics , series (stratigraphy) , interval (graph theory) , sample (material) , coverage probability , econometrics , algorithm , combinatorics , paleontology , materials science , chemistry , chromatography , composite material , biology
. 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.