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Web quantlets for time series analysis

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  • Härdle, Wolfgang
  • Kleinow, Torsten
  • Tschernig, Rolf

Abstract

Newly developed and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Moreover, their implementation requires substantial time, computing power as well as programming skills. The recent results on lag and bandwidth selection methods for nonlinear autoregressive time series models provide such a scenario. Application of these methods requires enormous computing resources if larger samples are considered. In this paper we suggest a method to provide empirical researchers with a fast access to new methods as well as to powerful computing environments. It is illustrated with a recently suggested nonparametric lag selection procedure based on CAFPE (Corrected Asymptotic Final Prediction Error). Our approach is based on the XploRe quantlet technology. Its worldwide Web usage is made possible by a specific client/server architecture. It allows researchers to use the quantlet computing service without knowing either the statistical computing language or the server location. Quantlets are accessed via standard WWW browsers or via a Java client which works like a standard desktop environment. This architecture allows a flexible scaling of time consuming computations on either client or server. The XploRe quantlet service is helpful in constructing research books and interactive teaching environments as the electronic version of this paper demonstrates.

Suggested Citation

  • Härdle, Wolfgang & Kleinow, Torsten & Tschernig, Rolf, 2000. "Web quantlets for time series analysis," SFB 373 Discussion Papers 2000,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:20001
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    References listed on IDEAS

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    1. L. Yang & R. Tschernig, 1999. "Multivariate bandwidth selection for local linear regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 793-815.
    2. Dahlhaus, R. & Neumann, M. & Von Sachs, R., 1997. "Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes," SFB 373 Discussion Papers 1997,34, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Hardle, W. & Tsybakov, A., 1997. "Local polynomial estimators of the volatility function in nonparametric autoregression," Journal of Econometrics, Elsevier, vol. 81(1), pages 223-242, November.
    4. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Lag Selection for Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(4), pages 457-487, July.
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    Cited by:

    1. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Neuwirth, E., 2003. "Computational Statistics with Spreadsheets Towards Efficiency, Reproducibility and Security," SFB 373 Discussion Papers 2003,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Rönz, Bernd, 2003. "E-learning, e-teaching of statistics: A new challenge," SFB 373 Discussion Papers 2003,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Kleinow, Torsten & Lehmann, Heiko, 2002. "Client/server based statistical computing," SFB 373 Discussion Papers 2002,49, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Härdle, Wolfgang & Rönz, Bernd, 2002. "E-learning / e-teaching of statistics: Students' and teachers' views," SFB 373 Discussion Papers 2002,84, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Rönz, Bernd, 2001. "MM*Stat - a multimedia tool for teaching of statistics," SFB 373 Discussion Papers 2001,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.
    7. Härdle, Wolfgang & Lehmann, Heiko & Rönz, Bernd, 2001. "MM*STAT: Eine interaktive Einführung in die Welt der Statistik," SFB 373 Discussion Papers 2001,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

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