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On the Vector Autoregressive Sieve Bootstrap
Author(s) -
Meyer Marco,
Kreiss JensPeter
Publication year - 2015
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/jtsa.12090
Subject(s) - mathematics , sieve (category theory) , autoregressive model , resampling , statistic , series (stratigraphy) , range (aeronautics) , residual , statistics , vector autoregression , econometrics , algorithm , combinatorics , paleontology , materials science , composite material , biology
The concept of autoregressive sieve bootstrap is investigated for the case of vector autoregressive (VAR) time series. This procedure fits a finite‐order VAR model to the given data and generates residual‐based bootstrap replicates of the time series. The paper explores the range of validity of this resampling procedure and provides a general check criterion, which allows to decide whether the VAR sieve bootstrap asymptotically works for a specific statistic or not. In the latter case, we will point out the exact reason that causes the bootstrap to fail. The developed check criterion is then applied to some particularly interesting statistics.