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A GOODNESS‐OF‐FIT TEST FOR AUTOREGRESSIVE MOVING‐AVERAGE MODELS BASED ON THE STANDARDIZED SAMPLE SPECTRAL DISTRIBUTION OF THE RESIDUALS
Author(s) -
Velilla Santiago
Publication year - 1994
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.1467-9892.1994.tb00218.x
Subject(s) - goodness of fit , mathematics , statistics , autoregressive model , anderson–darling test , sample (material) , kolmogorov–smirnov test , invertible matrix , autoregressive–moving average model , econometrics , statistical hypothesis testing , chemistry , chromatography , pure mathematics
. A stochastic process derived from the standardized sample spectral density of the residuals of a causal and invertible ARMA( p, q ) model is introduced to construct a goodness‐of‐fit procedure. The test statistics considered have a proper limiting distribution which is free of unknown parameters and which, unlike some well‐known goodness‐of‐fit statistics based on the residuals, does not depend on the sample size.