List of Publications

Statistics Netherlands publication period (2020 - current)


Links to other publications 1, 2, 3, 4, 5, 6.

Daas, P., Jansen, J. (2020) Model degradation in web derived text-based models. Paper for the 3rd International Conference on Advanced Research Methods and Analytics (CARMA), pp 77-84, doi.org/10.4995/CARMA2020.2020.11560 (paper).

Daas, P.J.H., van der Doef, S. (2020) Detecting Innovative Companies via their Website. Statistical Journal of IAOS 36(4), pp. 1239-1251, doi/10.3233/SJI-200627. (link).

Daas, P.J.H. (2020) Developing a Corona sentiment indicator: Methodological justification (in Dutch). CBS-report. (report).

Daas, P., Maslankowski, J., Salgado, D., Quaresma, S., Tuoto, T., Di Consiglio, L., Brancato, G., Righi, P., Six, M., Kowarik, A. (2020) First draft of the Methodological report. Deliverable K5, Workpackage K, ESSnet Big Data II, 17 June 2020. (report).

De Broe, S., Struijs, P., Daas, P., van Delden, A., Burger, J., van den Brakel, J., ten Bosch, O., Zeelenberg, K, Ypma, W.(2020) Updating the Paradigm of Official Statistics: New Quality Criteria for Integrating New Data and Methods in Official Statistics. CBDS-working paper 02-20. Statistics Netherlands, Heerlen/The Hague. paper).

Braaksma, B., Daas, P., Raaijmakers, S., Geurts, A., Meyer-Vitali, A. (2020) AI-Supported Innovation Monitoring. Paper for the TAILOR workshop 2020, Sept. 4. (paper).

Daas, P. and Puts, M. (2020) ISI IASS Webinar on Survey and Big data interactions. Video on GoToStage.com link.

De Broe, S., Struijs, P., Daas, P., van Delden, A., Burger, J., van den Brakel, J., ten Bosch, O., Zeelenberg, K, Ypma, W.(2020) Updating the Paradigm of Official Statistics: New Quality Criteria for Integrating New Data and Methods in Official Statistics. Statistical Journal of IAOS, accepted for publication.

Daas, P., Maslankowski, J., Salgado, D., Quaresma, S., Tuoto, T., Di Consiglio, L., Brancato, G., Righi, P., Six, M., Weinauer, M., Kowarik, A. (2020) Revised version of the Methodological report. Deliverable K9, Workpackage K, ESSnet Big Data II, 17 November 2020. (report).

Daas, P., Puts, M., Maslankowski, J., Salgado, D., Quaresma, S., Tuoto, T., Di Consiglio, L., Brancato, G., Righi, P., Six, M., Kowarik, A. (2020) Report describing the methodological steps of using big data in official statistics with a section on the most important research questions for the future including guidelines. Deliverable K10, Workpackage K, ESSnet Big Data II, 20 November 2020. (report).

Maslankowski, J., Salgado, D., Quaresma, S., Ascari, G., Brancato, G., Di Consiglio, L., Righi, P., Tuoto, T., Daas, P., Weinauer, M., Six, M., Kowarik, A. (2020) Report describing the quality aspects of the different pilots and the way forward. Deliverable K11, Workpackage K, ESSnet Big Data II, 24 November 2020. (report).

Puts, M.J.H., Daas, P.J.H.. (2021) Unbiased Estimations Based on Binary Classifiers: A Maximum Likelihood Approach. Abstract for the 2021 Symposium on Data Science and Statistics, Machine Learning session. (abstract, paper).

Daas, P.J., de Wolf, N.J. (2021). Identifying different types of companies via their website text. Abstract for the Symposium on Data Science and Statistics (SDSS) 2021, online, USA. (online abstract).

Daas, P.J.H., van der Doef, S. (2021) Using Website Texts to detect Innovative Companies. CBDS discussion paper 01-21. (report).

Daas, P., Schulte Nordholt, E, Tennekes, M., Ossen, S. (2021) Evaluation of the Quality of Administrative Data Used in the Dutch Virtual Census, Chapter 3, pp. 63-82. In: Administrative Records for Survey Methodology, Eds: Chun, A.Y., Larsen, M.D., Durrant, G., Reiter, J.P., Wiley, USA.

Puts, M. and Daas, P. (2021) EMOS Webinar on Machine Learning from a statistical perspective. Video on Youtube.com (video).

De Broe, S., ten Bosch, O., Daas, P., Buiten, G., Laevens, B., Kroese, B. (2021) The need for timely official statistics: the pandemic as a driver for innovation. Paper for the Big Data Matters 3 conference, Statistics Netherlands. online paper and link to publication.

Puts, M., Daas, P. (2021) Machine Learning from the Perspective of Official Statistics. The Survey Statistician 84. pp. 12-17. (paper).

Daas, P. (2021) Identifying different types of companies via their website texts. The Summer School on Survey Statistics 2021, On-line keynote speach. Video on Youtube.com (video).

The list of publications starts here. My presentations are also shared on SlideShare.