Arbeitspapier
Model order selection in seasonal/cyclical long memory models
We propose an automatic model order selection procedure for k-factor GARMA processes. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, we introduce a generalized version of Walker's large sample g-test that allows to test for persistent periodicity in stationary ARMA processes. Our simulation studies show that the procedure performs well in identifying the correct model order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been subject of several forecasting exercises.
- Language
-
Englisch
- Bibliographic citation
-
Series: Diskussionsbeitrag ; No. 535
- Classification
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Model Evaluation, Validation, and Selection
- Subject
-
Seasonal Long Memory
k-factor GARMA processes
Model selection
Electricity loads
- Event
-
Geistige Schöpfung
- (who)
-
Leschinski, Christian
Sibbertsen, Philipp
- Event
-
Veröffentlichung
- (who)
-
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät
- (where)
-
Hannover
- (when)
-
2014
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
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Object type
- Arbeitspapier
Associated
- Leschinski, Christian
- Sibbertsen, Philipp
- Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät
Time of origin
- 2014
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