Time Series Data Library The Time Series Data Library is a col­lec­tion of about 800 time series that I have main­tained since about 1992, and hosted on my per­sonal web­site. It includes data from a lot of time series text­books, as well as many other series that I’ve either col­lected for stu­dent projects or help­ful peo­ple have sent to me. I’ve now moved the col­lec­tion onto Data­Mar­ket which pro­vides much bet­ter facil­i­ties for main­tain­ing and using time series data. You can eas­ily search the col­lec­tion, graph any series, fil­ter by sea­sonal period, and so on. You can also export data in many for­mats. Each data set has its own short link; for exam­ple, the famous Cana­dian lynx data is at http://​data​.is/​K​y69xY.

References in zbMATH (referenced in 20 articles )

Showing results 1 to 20 of 20.
Sorted by year (citations)

  1. Di, Jianing; Gangopadhyay, Ashis: A data-dependent approach to modeling volatility in financial time series (2015)
  2. Gillard, J.W.; Zhigljavsky, A.A.: Stochastic algorithms for solving structured low-rank matrix approximation problems (2015)
  3. Pereira, André G.C.; de Andrade, Bernardo B.: On the genetic algorithm with adaptive mutation rate and selected statistical applications (2015)
  4. Luo, Wei; Gallagher, Marcus; Wiles, Janet: Parameter-free search of time-series discord (2013)
  5. Murlidharan, Vijayalakshmi; Menezes, Bernard: Frequent pattern mining-based sales forecasting (2013)
  6. Nandi, Swagata; Kundu, Debasis: Estimation of parameters of partially sinusoidal frequency model (2013)
  7. Gan, Min; Peng, Hui; Dong, Xue-Ping: A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction (2012)
  8. Hanzák, Tomáš: Holt-Winters method with general seasonality (2012)
  9. Ragulskis, Minvydas; Navickas, Zenonas; Palivonaite, Rita; Landauskas, Mantas: Algebraic approach for the exploration of the onset of chaos in discrete nonlinear dynamical systems (2012)
  10. Kharin, Yuriy S.; Voloshko, Valeriy A.: Robust estimation of AR coefficients under simultaneously influencing outliers and missing values (2011)
  11. Štěpnička, Martin; Dvořák, Antonín; Pavliska, Viktor; Vavříčková, Lenka: A linguistic approach to time series modeling with the help of F-transform (2011)
  12. Tang, Yongchuan; Lawry, Jonathan: A prototype-based rule inference system incorporating linear functions (2010)
  13. Petris, Giovanni; Petrone, Sonia; Campagnoli, Patrizia: Dynamic linear models with R (2009)
  14. Tang, Yongchuan; Lawry, Jonathan: Linguistic modelling and information coarsening based on prototype theory and label semantics (2009)
  15. Ghazali, R.; Hussain, A.J.; Liatsis, P.; Tawfik, H.: The application of ridge polynomial neural network to multi-step ahead financial time series prediction (2007)
  16. Lawry, Jonathon: Modelling and reasoning with vague concepts. With a foreword by Didier Dubois. (2006)
  17. Rakotomamonjy, Alain; Canu, Stéphane: Frames, reproducing kernels, regularization and learning (2005)
  18. Baragona, R.; Battaglia, F.; Cucina, D.: Fitting piecewise linear threshold autoregressive models by means of genetic algorithms (2004)
  19. Cortez, Paulo; Rocha, Miguel; Neves, José: Genetic and evolutionary algorithms for time series forecasting (2001)
  20. Zhang, G.P.; Berardi, V.L.: Time series forecasting with neural network ensembles: an application for exchange rate prediction (2001)