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  • Home
  • Publications
  • Springer Book
    • Table of Content
    • Chapter 1
    • Chapter 2
    • Chapter 3
    • Chapter 4
    • Chapter 5
    • Chapter 6
    • Chapter 7
    • Chapter 8
    • Chapter 9
    • Chapter 10
    • Chapter 11
    • Chapter 12
    • Errata
    • Reviews
  • DATA SETS
  • CONTACT
Picture

Chapter 10: Forecasting

Data Set
SCMI-HDR.dat
Computer Codes
​Examples:  
Example_10-2.zip  
​Example_10-3.zip
Example_10-4.zip
Example_10-6.zip  
Example_10-7.zip 
Example_10-8.zip 
​Section10-1-1.zip

Exercises:
Exercise_10-10.zip   
​Exercise_10-11b.zip 
Exercise_10-12.zip​   

Miscellanea:
Pan-Politis.zip                           
Regions.zip    

​Figures 
Figures-Chapter-10-exercises.zip        
Figures-Chapter-10-exercises-jpg.zip 
​

(R code)
(F code)
(M code)
(RATS and M codes)
(C source code and executable)
​(R code)
(F code)

​
(R code)
(R code)
(M code)


(R code)
(G code)

​
​(EPS format)
​(JPEG format)
Links to  Websites with  Supplementary Material
  • Short-term forecasting of  electricity spot prices has been the topic of many research papers.; see, e.g.,  Rafał Weron's homepage. To replicate results in the paper by Misiorek et al. (2006, Stud. Nonlinear Dyn. E.); see  the RePEc website for MATLAB code.autots-r-code.zip
  • EViews code and a data worksheet  for replicating results in the paper by Stevenson et al. (2006, Stud. Nonlinear Dyn. E.) are available at the journal paper website (authorized access). Nord Pool hourly electricity price data are here (authorized access).
  • The R-autots package (2011, Comm. Korean Statistical Soc.) can be  used for automatic model selection for both linear and nonlinear time series models by minimizing prediction errors and checking model-adequacy. Note that the package works in an old version of R(2.15.1) under fGarch (<=2110.80.1), tsDyn(<=0.8-1), and forecast (<=3.10).
Last modified: May 2023

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