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 32 articles )

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  1. Cerqueira, Vitor; Torgo, Luis; Mozetič, Igor: Evaluating time series forecasting models: an empirical study on performance estimation methods (2020)
  2. Saleena, A. J.; Jessy John, C.: A new hybrid model based on triple exponential smoothing and fuzzy time series for forecasting seasonal time series (2020)
  3. Cerqueira, Vitor; Torgo, Luís; Pinto, Fábio; Soares, Carlos: Arbitrage of forecasting experts (2019)
  4. Kovács, György; Sebestyen, Gheorghe; Hangan, Anca: Evaluation metrics for anomaly detection algorithms in time-series (2019)
  5. Yazdanbakhsh, Omolbanin; Dick, Scott: FANCFIS: fast adaptive neuro-complex fuzzy inference system (2019)
  6. Landauskas, Mantas; Navickas, Zenonas; Vainoras, Alfonsas; Ragulskis, Minvydas: Weighted moving averaging revisited: an algebraic approach (2017)
  7. Sadaei, Hossein Javedani; Guimarães, Frederico Gadelha; José da Silva, Cidiney; Lee, Muhammad Hisyam; Eslami, Tayyebeh: Short-term load forecasting method based on fuzzy time series, seasonality and long memory process (2017)
  8. He, Xiaoxu; Shao, Chenxi; Xiong, Yan: A non-parametric symbolic approximate representation for long time series (2016)
  9. Seneta, Eugene; Ku, Simon: Unique decomposition of low-order time series (2016)
  10. Di, Jianing; Gangopadhyay, Ashis: A data-dependent approach to modeling volatility in financial time series (2015)
  11. Gillard, J. W.; Zhigljavsky, A. A.: Stochastic algorithms for solving structured low-rank matrix approximation problems (2015)
  12. Pereira, André G. C.; de Andrade, Bernardo B.: On the genetic algorithm with adaptive mutation rate and selected statistical applications (2015)
  13. Lemos, Andre; Caminhas, Walmir; Gomide, Fernando: Evolving intelligent systems: methods, algorithms and applications (2013) ioport
  14. Luo, Wei; Gallagher, Marcus; Wiles, Janet: Parameter-free search of time-series discord (2013)
  15. Murlidharan, Vijayalakshmi; Menezes, Bernard: Frequent pattern mining-based sales forecasting (2013)
  16. Nandi, Swagata; Kundu, Debasis: Estimation of parameters of partially sinusoidal frequency model (2013)
  17. Aminghafari, Mina; Poggi, Jean-Michel: Nonstationary time series forecasting using wavelets and kernel smoothing (2012)
  18. Gan, Min; Peng, Hui; Dong, Xue-Ping: A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction (2012)
  19. Hanzák, Tomáš: Holt-Winters method with general seasonality (2012)
  20. Ragulskis, Minvydas; Navickas, Zenonas; Palivonaite, Rita; Landauskas, Mantas: Algebraic approach for the exploration of the onset of chaos in discrete nonlinear dynamical systems (2012)

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