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Results: 103
Number of items: 103
  • Open Access
    Meertens, Q. A. (2021). Misclassification bias in statistical learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Buiten, G., Diks, C., Faber, A., Heemskerk, E., Mattsson, C., Takes, F., & Sloot, P. (2021). Netwerkanalyse biedt nieuwe inzichten voor clustergericht energiebeleid. Economisch-Statistische Berichten, 106(4804), 586-588. https://esb.nu/esb/20068796/netwerkanalyse-biedt-nieuwe-inzichten-voor-clustergericht-energiebeleid
  • Open Access
    Li, H. (2021). Dependence in financial and high-dimensional time series. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Turco, E. M. (2021). The stagnation-financialization paradox: Understanding a modern puzzle through complex systems. [Thesis, fully internal, Universiteit van Amsterdam, Università Cattolica del Sacro Cuore].
  • Meertens, Q. A., Diks, C., & Takes, F. (2020, December 7). Global business register used to estimate cross-border internet purchases within the EU [Data set]. Universiteit van Amsterdam. https://doi.org/10.21942/uva.13303082.v1
  • Linardi, F., Diks, C., van der Leij, M., & Lazier, I. (2020). Dynamic interbank network analysis using latent space models. Journal of Economic Dynamics & Control, 112, Article 103792. https://doi.org/10.1016/j.jedc.2019.103792
  • Diks, C., & Fang, H. (2020). Comparing density forecasts in a risk management context. International Journal of Forecasting, 36(2), 531-551. https://doi.org/10.1016/j.ijforecast.2019.07.006
  • Open Access
    Meertens, Q. A., Diks, C. G. H., van den Herik, H. J., & Takes, F. W. (2020). A data‐driven supply‐side approach for estimating cross‐border Internet purchases within the European Union. Journal of the Royal Statistical Society. Series A (Statistics in Society), 183(1), 61-90. https://doi.org/10.1111/rssa.12487
  • Open Access
    Diks, C., & Fang, H. (2020). A Consistent Nonparametric Test for Granger Non-Causality Based on the Transfer Entropy. Entropy, 22(10), Article 1123. https://doi.org/10.3390/e22101123
  • Meertens, Q. A., Diks, C. G. H., van den Herik, H. J., & Takes, F. W. (2019). A Bayesian Approach for Accurate Classification-Based Aggregates. In T. Berger-Wolf, & N. Chawla (Eds.), Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 306-314). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611975673.35
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