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Time Series Models in Non‐Normal Situations: Symmetric Innovations
Author(s) -
Tiku M. L.,
Wong WingKeung,
Vaughan David C.,
Bian Guorui
Publication year - 2000
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 - 10.1111/1467-9892.00199
Subject(s) - estimator , mathematics , series (stratigraphy) , maximum likelihood , m estimator , statistics , econometrics , paleontology , biology
We consider AR( q ) models in time series with non‐normal innovations represented by a member of a wide family of symmetric distributions (Student's t ). Since the ML (maximum likelihood) estimators are intractable, we derive the MML (modified maximum likelihood) estimators of the parameters and show that they are remarkably efficient. We use these estimators for hypothesis testing, and show that the resulting tests are robust and powerful.