Chapter 1: Introduction and Some Basic Concepts

Data Sets
Chapter-1-data.zip
DeltaC.dat
DeltaO.dat
EEG.dat
ENSO.dat
Magnetic_field.dat
​USunemplmnt_first_dif.dat
USunemplmnt251.dat

​Note: Most of the data  files are one long column. Some data files are in multicolumn formats.  A few data files contain brief information about its source and/or the names of the variables. Hence, it would be a good idea to look at the file before you use it. The data sets can also be found at the publisher's Web site http://extras.springer.com/.

Computer Codes
​Examples:
Example_1-5.zip  
Example_1-8.zip  
​Example_1-9.zip
​
​Exercises:
Exercise_1-8-G.zip​
Exercise_1-8-M.zip​

Miscellaneous:
​Resnick-vdBerg-test.txt 

Figures 
Figures-Chapter-1-exercises.zip         
Figures-Chapter-1_exercises-jpg.zip   ​

​
​(R code)
(F code and renamed exe files)
(Data & M code)

​
(G code)
(M code)


​(S-Plus code and renamed prg file)

​
(EPS format)
​(JPEG format)

​Links to  Websites with  Supplementary Material

• Data files and GAUSS codes to accompany  Franses and Van Dijk (2000), Nonlinear Time Series Models in Empirical Finance, (Cambridge University Press, UK) can be downloaded from: people.few.eur.nl/djvandijk/nltsmef/nltsmef.htm.
• Click on the following link for getting access to the website of TSTOOL, a MATLAB package  for analyzing time series by nonlinear dynamic methods.
• Scilab is a matrix-oriented software package for numerical computation similar to GAUSS and MATLAB. Scilab is released as open source and is available for download free of charge. Grocer is an econometrics toolbox for Scilab. ​
• Click on the following link for getting access to R-codes to accompany the book by  Douc, Moulines and Stoffer (2014), Nonlinear Time Series: Theory, Methods, and Applications with R Examples (Chapman & Hall, CRC Press). See also David Stoffer's homepage  for some data files, papers, and software.
• Click on the following link for getting access to the NASA Space Science Data Coordinated Archive.
• Click on the following link for getting access to Mike West's homepage with software and  data sets from Mike's group and co-authors.
• Click on the following link for getting access to the Climate Prediction Center database of the U.S. National Oceanic and Atmospheric Administration (NOAA).
• Click on the following link for getting access to Rob Hyndman's Time Series Data Library, now hosted on DataMarket.com.
• Click on the following link for getting access to the time series data sets for the Hipel-McLeod (1994) book. The book can be freely downloaded from: http://www.stats.uwo.ca/faculty/aim/1994Book/. Associated with the book is the McLeod-Hipel Time Series Package for linear time series analysis; see http://www.stats.uwo.ca/faculty/mcleod/epubs/mhts/default.htm.
• Click on the following link for getting access to the website of the TISEAN package (nonlinear dynamic methods).  Note, there  is an interface to the R package.
• Click on the following link for getting access to Matjavz Perc's  homepage with executable computer codes for nonlinear dynamic time methods.
• Click one of the following two links for the quarterly U.S. unemployment time series: U.S. Bureau of Labor Statistics,  and  Federal Reserve Bank of St. Louis.
• Click on the following link for other EEG time series.
• Click on the following link for getting access to David Ubilava’s website. Click on the following link for getting access to the R code and the ENSO data file to replicate main results in the paper by Ubilava (2012, Agricultural Economics).
• Click on the following link for getting access to extensive information on the Ocean Drilling Program. .
• Click on the following link for getting access to Serena Ng’s homepage with GAUSS code (abusively called MATLAB code) for the Bai-Ng (2005, JBES) tests for skewness, kurtosis and normality.
• The five data sets used in The Santa Fe Institute Time Series Prediction and Analysis Competition are available at:
  www-psych.stanford.edu/~andreas/Time-Series/SantaFe.html. The competition is described in the book Time Series Prediction: Forecasting the Future and Understanding the Past,  A.S. Weigend and N.A. Gershenfeld (Eds.), Reading, MA: Addison-Wesley, 1994. 
• Click on the following link for getting access to Michael Small's homepage with MATLAB code to accompany his book Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance. Nonlinear Science Series A, vol. 52. World Scientific, 2005. One may also check out the MATLAB htsa package on github (launched November 2015), a highly comprehensive package of  time-series analysis methods.
• The website of the course Non-Linear Time Series Analysis (Lunds Universitet, Sweden)  provides access to  MATLAB and R-scripts for solving the computer lab exercises.
• Danny Kaplan's website provides access to a small collection of MATLAB software implementing several techniques of nonlinear dynamics time series analysis.
• Andreas Galka's homepage provides a  list with links (some of them are outdated) to individuals and research groups working in the area of  (non)linear time  series analysis and neuroscience data analysis.
• Thomas Mikosch' homepage provides a link to a 2004-Workshop on Non-Linear Time Series Modeling.  Click on the following link for getting access to the website of the  2011-IMS Workshop on Recent Advances on Nonlinear Time Series Analysis. The website Nonlinear Time Series Analysis - Thresholding and Beyond provides information about a 2014-LSE Conference held in honor of  Professor Howell Tong to celebrate his 70th birthday.
• Click on the following link for downloading C source code  related to the paper by Diks et al. (1996, Physical Review). FORTRAN77 code for computing the proposed test statistic with MC simulated data, is here.