Chapter 6: Model Estimation, Selection, and Checking
Data Sets
Chapter_6-data.zip
Example62_res.dat
HSI_returns.dat
HSI-daily-stockprices-2010-T251.dat
USgnp.dat
WaterTable-Precipitation.dat
Well-1-6.zip
Chapter_6-data.zip
Example62_res.dat
HSI_returns.dat
HSI-daily-stockprices-2010-T251.dat
USgnp.dat
WaterTable-Precipitation.dat
Well-1-6.zip
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Computer Codes
Examples: Example_6-1.zip Example_6-2.zip Example_6-3.zip Example_6-4.zip Example_6-5.zip Example_6-6.zip Example_6-7.zip Example_6-8.zip Section 6.4: TARSO.zip Exercises: Exercise_6-5.m Exercise_6-5-remark.r Exercise_6-6.m Exercise_6-8.r Exercise_6-9.m Miscellanea: Amendola-Francq.zip Bagnato.zip Ling-Tong.zip STAR3-32bit.zip Strikholm-Terasvirta.zip TARfit.src Threshold models Genetic Algorithms (GA) (Executable C codes): DTGARCH-GA.zip MSETAR-GA.zip PLTAR-GA.zip SETAR-GA.zip Giovanis-GA.zip Multiple-regime-GA.zip Figures Figures-Chapter-6-exercises.zip Figures-Chapter-6-exercises-jpg.zip |
(M code) (M and R codes) (F code) (R code) (M code) (Renamed exe and dll files; see the Readme.txt file) (M code) (G code) (F code) (M code) (R code) (M code) (R code) (M code) (R code) (M code) (F code) (To execute the program, see the files Readme.txt and Password-STAR3.txt) (G code) (G code) (To execute the programs rename the files with the extension ... .exe.txt and ... .dll.txt; see the Readme.txt file) (M code) (M code) (EPS format) (JPEG format) |
Links to Websites with Supplementary Material
- Click on the following link for getting access to the Ox package TSM (Time Series Modelling) by James Davidson. TSM runs under Ox Console (32-bit) and is offered free for academic and educational purposes. For the 64-bit version, it requires a licence for the commercial package Ox Professional. TSM will estimate and forecast ARIMA and ARFIMA models, several GARCH, FIGARCH, APARCH and EGARCH variants, BL models, Markov switching models, and STAR models.
- Click on the following link for getting access to the web page of Christian Francq for R and MATHEMATICA codes associated with the results in the paper by Amendola and Francq (2009). Reference: Amendola, A. and Francq, C. (2009). Concepts and tools for nonlinear time series modelling. In E. Kontoghiorghes and D. Belsley (Eds.) Handbook of Computational Econometrics, Wiley, New York, pp. 377-427. See also the MPRA working paper at mpra.ub.uni-muenchen.de/15140 and for a more recent version htttp://mpra.ub.uni-muenchen.de/16668/.
- Click on the following link for getting access to the web page of Tomáš Bacigál with MATHEMATICA codes associated with results in his PhD thesis "Advanced methods of time series modelling and their application in geodesy". The GPS data set analyzed in Bacigál (2004, J. Electrical Engineering) is here.
- The original GAUSS codes for replicating the results in Van Dijk et al. (2002, Econometric Reviews) are here.
- New STAR model selection results are given by Maringer and Meyer (2008, Stud. Nonlinear Dyn. E.). For data sets and results, see the journal article website (authorized access). The performance of information criteria for SETAR and STAR model selection are evaluated by Rinke and Sibbertsen (2016, Stud. Nonlinear Dyn. E.). MATLAB code for replicating this study is available at the journal article website (authorized access).