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APPROXIMATE SIMULTANEOUS SIGNIFICANCE INTERVALS FOR RESIDUAL AUTOCORRELATIONS OF AUTOREGRESSIVE MOVING‐AVERAGE TIME SERIES MODELS
Author(s) -
Hosking J. R. M.,
Ravishanker Nalini
Publication year - 1993
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.1467-9892.1993.tb00127.x
Subject(s) - mathematics , autocorrelation , autoregressive model , bonferroni correction , residual , series (stratigraphy) , statistics , goodness of fit , moving average model , autoregressive–moving average model , econometrics , moving average , time series , autoregressive integrated moving average , algorithm , paleontology , biology
. Bonferroni‐type inequalities are used to approximate probabilities of the joint distribution of residual autocorrelation coefficients from an autoregressive moving‐average time series model. The approximations are useful for testing the goodness of fit of the model:they can be used to find critical values of a test of whether the largest residual autocorrelation is significantly different from zero. The approximation based on the first‐order Bonferroni inequality is simple to use and adequate in practice.

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