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Correlogram Analysis Revisited
Author(s) -
Wallis J. R.,
Matalas N. C.
Publication year - 1971
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr007i006p01448
Subject(s) - correlogram , autocorrelation , independence (probability theory) , autoregressive model , mathematics , sequence (biology) , statistics , hurst exponent , lag , econometrics , persistence (discontinuity) , interpretation (philosophy) , statistical physics , computer science , biology , geology , physics , genetics , computer network , geotechnical engineering , programming language
Consideration of the Hurst coefficient h offers new insight into the interpretation of observed correlograms for streamflow sequences. Autoregressive models, for which h = ½, cannot reproduce the structures of those correlograms. The structures are symptomatic of long‐term persistence as indicated by observed values of h being greater than ½. The tendency has been to test a sequence for independence, and if the hypothesis of independence is unacceptable, then (1) the generating process for the sequence is approximated by a short memory process, and (2) variations in the high lag serial correlation coefficients are ascribed to chance. If indeed the sequences are generated by long memory processes, then the powers of most independence tests are low for short records. Consequently, correlograms may be useful indicators of long‐term persistence when more formal tests give contrary results.