P.J.F. (Patrick) Groenen

Full Professor
Erasmus School of Economics
Erasmus University Rotterdam
Member ERIM
Field: Marketing
Affiliated since 2002

Patrick J.F. Groenen is a professor of statistics at the Erasmus School of Economics (ESE).



Professor Groenen's work focuses on a range of issues relating to exploratory multivariate analysis and multidimensional scaling and their numerical algorithms.



He is the co-author of a textbook on multidimensional scaling published by Springer and has published articles in the top peer-reviewed journals including, among others, the Journal of Marketing Research, Computational Statistics and Data Analysis, Psychological Methods, Psychometrika, the Journal of Classification, the British Journal of Mathematical and Statistical Psychology, and the Journal of Empirical Finance.

  • Heij, C., Exterkate, P., Groenen, P.J.F. & Dijk, D.J.C. van (2016). Nonlinear forecasting with many predictors using kernel ridge regression. International Journal of Forecasting, To appear.
  • Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, JJ, Pers, TH, Rietveld, C.A., Turley, P, Chen, G-B, Emilsson, V, Meddens, S.F.W., Oskarsson, S, Pickrell, J.K., Thom, K, Timshel, P, Vlaming, R. de, Lee, S.J. van der, Amin, N., Rooij, F.J.A. van, Duijn, C.M. van, Groenen, P.J.F., Thurik, A.R., Tiemeier, H.W., Uitterlinden, A.G., Hofman, A., SSGAC, The, Yang, J., Johannesson, M., Visscher, P.M., Esko, T, Koellinger, P.D., Cesarini, D.A. & Benjamin, D.J. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, Under rev..
  • Herk, H. van, Schoonees, P.C., Groenen, P.J.F. & Rosmalen, J.M. van (2015). Competing for the Same Value Segments: Explaining the Volatile Dutch Political Landscape. : ERIM Report Series Research in Management.
  • Tenenhaus, M., Tenenhaus, A. & Groenen, P.J.F. (2015). Regularized Consensus PCA. (Extern rapport). : arXiv.

Key Publications (12)

  • Loos, M.J.H.M. van der, Koellinger, P.D., Groenen, P.J.F., Rietveld, C.A., Rivadeneira, F., Rooij, F.J.A. van, Uitterlinden, A.G., Hofman, A. & Thurik, A.R. (2011). Candidate gene studies and the quest for the entrepreneurial gene. Small Business Economics, 37 (3), 269-275. doi: http://dx.doi.org/10.1007/s11187-011-9339-2[go to publisher's site]
  • Heij, C., Dijk, D.J.C. van & Groenen, P.J.F. (2011). Forecasting with leading indicators by means of the principal covariate index. Journal of Business Cycle Measurement and Analysis, 4 (1), 73-92.[go to publisher's site]
  • Heij, C., Dijk, D.J.C. van & Groenen, P.J.F. (2011). Real-time macroeconomic forecasting with leading indicators: An empirical comparison. International Journal of Forecasting, 27 (2), 466-481. doi: http://dx.doi.org/10.1016/j.ijforecast.2010.04.008[go to publisher's site]
  • Beauchamp, J.P., Cesarini, D., Johannesson, M., Loos, M.J.H.M. van der, Koellinger, P.D., Groenen, P.J.F., Fowler, J.H., Rosenquist, J.N., Thurik, A.R. & Christakis, N.A. (2011). Molecular genetics and economics. Journal of Economic Perspectives, 25 (4), 57-82. doi: http://dx.doi.org/10.1257jep.25.4.57[go to publisher's site]
  • Rosmalen, J.M. van, Herk, Hester van & Groenen, P.J.F. (2010). Identifying response styles: a latent-class bilinear multinomial logit model. Journal of Marketing Research, 47 (1), 157-172. doi: http://dx.doi.org/10.1509/jmkr.47.1.157[go to publisher's site]
  • Koellinger, P.D., Loos, M.J.H.M. van der, Groenen, P.J.F., Thurik, A.R., Rivadeneira, F., Rooij, F.J.A. van, Uitterlinden, A.G. & Hofman, A. (2010). Genome-wide assocation studies in economics and entrepreneurship research: promises and limitations. Small Business Economics, 35 (1), 1-18. doi: http://dx.doi.org/10.1007/s11187-010-9286-3[go to publisher's site]
  • Rosmalen, J.M. van, Koning, A.J. & Groenen, P.J.F. (2009). Optimal scaling of interaction effects in generalized linear modelling. Multivariate Behavioral Research, 44 (1), 59-81. doi: http://dx.doi.org/10.1080/00273170802620048
  • Kagie, M., Wezel, M.C. van & Groenen, P.J.F. (2008). A graphical shopping interface based on product attributes. Decision Support Systems, 46 (1), 265-276. doi: http://dx.doi.org/10.1016/j.dss.2008.06.011[go to publisher's site]
  • Groenen, P.J.F., Nalbantov, G.I. & Bioch, J.C. (2008). SVM-Maj: a majorization approach to linear support vector machines with different hinge errors. Advances in Data Analysis and Classification, 2 (1), 17-43. doi: http://dx.doi.org/10.1007/s11634-008-0020-9
  • Deun, K. van & Groenen, P.J.F. (2005). Majorization algorithms for inspecting circles, ellipses, squares, rectangles, and rhombi. Operations Research, 53 (6), 957-967. doi: http://dx.doi.org/10.1287/opre.1050.0253[go to publisher's site]
  • Busing, F.M.T.A., Groenen, P.J.F. & Heiser, W.J. (2005). Avoiding degeneracy in multidimensional unfolding by penalizing on the coefficient of variation. Psychometrika, 70 (1), 71-98. doi: http://dx.doi.org/10.1007/s11336-001-0908-1
  • Tarakci, M., Greer, L.L. & Groenen, P.J.F. (2016). When does power disparity help or hurt group performance? Journal of Applied Psychology, Accepted. doi: http://dx.doi.org/10.1037/apl0000056
  • Schoonees, P.C., Velden, M. van de & Groenen, P.J.F. (2015). Constrained Dual Scaling for Detecting Response Styles in Categorical Data. Psychometrika, 80 (4), 968-994. doi: http://dx.doi.org/10.1007/s11336-015-9458-9
  • Vlaming, R. de & Groenen, P.J.F. (2015). The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics. BIOMED RESEARCH INTERNATIONAL. Retrieved from http://www.hindawi.com/journals/bmri/aip/143712/
  • Doering, A.K., Schwartz, S.H., Cieciuch, J., Groenen, P.J.F., Glatzel, V., Harasimczuk, J., Janowicz, N., Nyagolova, M., Scheefer, E.R., Allritz, M., Milfont, T.C. & Bilsky, W. (2015). Cross-cultural evidence of value structures and priorities in childhood. British Journal of Psychology, 106 (4), 675-699. doi: http://dx.doi.org/10.1111/bjop.12116
  • Groenen, P.J.F., Gardner-Lubbe, Sugnet & Le Roux, Niël (2015). Spline-based nonlinear biplots. Advances in Data Analysis and Classification, 9, 219-238. doi: http://dx.doi.org/10.1007/s11634-014-0179-1[go to publisher's site]
  • Tarakci, M., Ates, N.Y., Porck, J.P., van Knippenberg, D., Groenen, P.J.F. & Haas, M. de (2014). Strategic Consensus Mapping: A New Method for Testing and Visualizing Strategic Consensus Within and Between Teams. Strategic Management Journal, 35 (7), 1053-1069. doi: http://dx.doi.org/10.1002/smj.2151[go to publisher's site]
  • Gower, J.C., Groenen, P.J.F., Velden, M. van de & Vines, K. (2014). Better perceptual maps: Introducing explanatory icons to facilitate interpretation. Food Quality and Preference, 36, 61-69. doi: http://dx.doi.org/10.1016/j.foodqual.2014.01.004[go to publisher's site]
  • Sikorska, K., Lesaffre, E.M.E.H., Groenen, P.J.F. & Eilers, P.H.C. (2013). GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. Bmc Bioinformatics, 14 (166), 1-11. doi: http://dx.doi.org/10.1186/1471-2105-14-166
  • Rietveld, C.A., Medland, SE, Derringer, J, Yang, J., Esko, T, Martin, N.W., Westra, HJ, Shakhbazov, K, Abdellaoui, A, Agrawal, A., Albrecht, E, Alizadeh, B.Z., Amin, N., Barnard, J, Baumeister, SE, Benke, KS, Bielak, LF, Boatman, JA, Boyle, PA, Davies, G., Leeuw, C. de, Eklund, N, Evans, DS, Fehrmann, R, Fischer, K., Gieger, C, Gjessing, HK, Hägg, S, Harris, JR, Hayward, C, Holzapfel, C, Verbaas, C.A., Ingelsson, E, Jacobsson, B, Joshi, PK, Jugessur, A, Kaakinen, M, Kanoni, S, Karjalainen, J, Kolcic, I, Kristiansson, K, Kutalik, Z, Lahti, J, Lee, SH, Lin, P, Lind, PA, Liu, Y., Lohman, K, Loitfelder, M, McMahon, G, Marques Vidal, P, Meirelles, O, Milani, L, Myhre, R, Nuotio, ML, Oldmeadow, CJ, Petrovic, KE, Peyrot, WJ, Polasek, O, Quaye, L, Reinmaa, E, Rice, JP, Rizzi, TS, Schmidt, H., Schmidt, R., Smith, AV, Smith, JA, Tanaka, T, Terracciano, A, Loos, M.J.H.M. van der, Vitart, V, Völzke, H, Wellmann, J, Yu, L, Zhao, W, Allik, J, Attia, JR, Bandinelli, S, Bastardot, F, Beauchamp, J., Bennett, DA, Berger, K., Bierut, L, Boomsma, D.I., Bültmann, U, Campbell, H, Chabris, C.F., Cherkas, L, Chung, MK, Cucca, F, Andrade, M de, Jager, PL De, De Neve, J.E., Deary, IJ, Dedoussis, GV, Deloukas, P, Dimitriou, M, Eiriksdottir, G, Elderson, MF, Eriksson, JG, Evans, DM, Faul, JD, Ferrucci, L, Garcia, ME, Grönberg, H, Gudnason, V, Hall, P., Harris, JM, Harris, T.B., Hastie, ND, Heath, AC, Hernandez, DG, Hoffmann, W., Hofman, W.H.A., Holle, R, Holliday, EG, Hottenga, J.J., Iacono, WG, Illig, T, Järvelin, MR, Kähönen, M, Kaprio, J, Kirkpatrick, RM, Kowgier, M, Latvala, A, Launer, L.J., Lawlor, DA, Lehtimäki, T, Li, J., Lichtenstein, P., Lichtner, P, Liewald, DC, Madden, PA, Magnusson, PKE, Mäkinen, TE, Masala, M, McGue, M, Metspalu, A, Mielck, A., Miller, MB, Montgomery, GW, Mukherjee, S., Nyholt, DR, Oostra, B.A., Palmer, LJ, Palotie, A, Penninx, BWJH, Perola, M, Peyser, PA, Preisig, M, Räikkönen, K, Raitakari, OT, Realo, A, Ring, SM, Ripatti, S, Rivadeneira, F., Rudan, I, Rustichini, A, Salomaa, V, Sarin, AP, Schlessinger, D, Scott, R.J., Snieder, H, St Pourcain, B, Starr, JM, Sul, JH, Surakka, I, Svento, R, Teumer, A, Lifelines Cohort Study, THE, Tiemeier, H., Rooij, F.J.A. van, Van Wagoner, DR, Vartiainen, E, Viikari, J, Vollenweider, P, Vonk, JM, Waeber, G, Weir, DR, Wichmann, H-E., Widen, E, Willemsen, G, Wilson, JF, Wright, AF, Conley, D., Davey-Smith, G, Franke, L, Groenen, P.J.F., Hofman, A., Johannesson, M, Kardia, SLR, Krueger, RF, Laibson, D., Martin, NG, Meyer, MN, Posthuma, D, Thurik, A.R., Timpson, NJ, Uitterlinden, A.G., Duijn, C.M. van, Visscher, P.M., Benjamin, D.J., Cesarini, D. & Koellinger, P.D. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 240 (6139), 1467-1471. doi: http://dx.doi.org/10.1126/science.1235488[go to publisher's site]
  • Loos, M.J.H.M. van der, Haring, R, Rietveld, C.A., Baumeister, SE, Groenen, P.J.F., Hofman, A., Jong, F.H. de, Koellinger, P.D., Kohlmann, T., Nauck, M.A., Rivadeneira Ramirez, F., Uitterlinden, A.G., Rooij, F.J.A. van, Wallaschofski, H. & Thurik, A.R. (2013). Serum testosterone levels in males are not associated with entrepreneurial behavior in two independent observational studies. Physiology & Behavior, 119, 110-114. doi: http://dx.doi.org/10.1016/j.physbeh.2013.06.003[go to publisher's site]
  • Loos, M.J.H.M. van der, Rietveld, C.A., Eklund, N, Koellinger, P.D., Rivadeneira Ramirez, F., Abecasis, GR, Ankra-Badu, GA, Baumeister, SE, Benjamin, D.J., Biffar, R, Blankenberg, S, Boomsma, D.I., Cesarini, D., Cucca, F, Geus, E.J.C. de, Dedoussis, G, Deloukas, P, Dimitriou, M, Eiriksdottir, G, Eriksson, J, Gieger, C, Gudnason, V, Hoehne, B, Holle, R, Hottenga, J.J., Isaacs, A.J., Jarvelin, MR, Johannesson, M, Kaakinen, M, Kahonen, M, Kanoni, S, Laaksonen, MA, Lahti, J, Launer, L.J., Lehtimaki, T, Loitfelder, M, Magnusson, PKE, Naitza, S, Oostra, B.A., Perola, M, Petrovic, K, Quaye, L, Raitakari, O, Ripatti, S, Scheet, P, Schlessinger, D, Schmidt, CO, Schmidt, H., Schmidt, R., Senft, A., Smith, AV, Spector, T.D., Surakka, I, Svento, R, Terracciano, A, Tikkanen, E, van Duijn, CM, Viikari, J, Voelzke, Henry, Wichmann, H-E., Wild, PS, Willems, S.M., Willemsen, G, Rooij, F.J.A. van, Groenen, P.J.F., Uitterlinden, A.G., Hofman, A. & Thurik, A.R. (2013). The Molecular Genetic Architecture of Self-Employment. PLoS One (print), 8 (4), e60542. doi: http://dx.doi.org/10.1371/journal.pone.0060542[go to publisher's site]
  • Sikorska, K., Rivadeneira, F., Groenen, P.J.F., Hofman, A., Uitterlinden, A.G., Eilers, P.H.C. & Lesaffre, E. (2013). Fast linear mixed model computations for genome-wide association studies with longitudinal data. Statistics in Medicine, 32 (1), 165-180. doi: http://dx.doi.org/10.1002/sim.5517[go to publisher's site]
  • Cecere, S, Groenen, P.J.F. & Lesaffre, E.M.E.H. (2013). The Interval-Censored Biplot. Journal of Computational and Graphical Statistics, 22 (1), 123-134. doi: http://dx.doi.org/10.1080/10618600.2012.700874[go to publisher's site]
  • Velden, M. van de, Beuckelaer, A. de, Groenen, P.J.F. & Busing, F.M.T.A. (2013). Solving degeneracy and stability in nonmetric unfolding. Food Quality and Preference, 27 (1), 85-95. doi: http://dx.doi.org/10.1016/j.foodqual.2012.06.010[go to publisher's site]
  • Exterkate, P., Dijk, D.J.C. van, Heij, C. & Groenen, P.J.F. (2013). Forecasting the yield curve in a data-rich environment using the factor-augmented Nelson-Siegel model. Journal of Forecasting, 32 (2013), 193-214. doi: http://dx.doi.org/10.1002/for.1258[go to publisher's site]
  • Herk, Hester van, Groenen, P.J.F. & Rosmalen, J.M. van (2012). Waarden, segmenten en politieke partijen: Stabiliteit en verandering in de jaren nul. In K. Aarts & M. Wittenberg (Eds.), Nederland in de jaren nul (pp. 19-37). Amsterdam: Pallas, Amsterdam University Press.
  • Ates, N.Y., Tarakci, M., Porck, J.P., van Knippenberg, D. & Groenen, P.J.F. (2012). How Middle Managers Get Subordinates on Board? The Moderating Role of Strategic Alignment with CEO. In ERIM Report Series.
  • Cecere, S, Leroy, R, Groenen, P.J.F., Lesaffre, E. & Declerck, D (2012). Estimating emergence sequences of permanent teeth in Flemish schoolchildren using interval-censored biplots: a graphical display of tooth emergence sequences. Community Dentistry and Oral Epidemiology, 40 (suppl.1), 50-56. doi: http://dx.doi.org/10.1111/j.1600-0528.2011.00666.x[go to publisher's site]
  • Nalbantov, G.I., Groenen, P.J.F. & Smirnov, E. (2012). A Comparative Analysis of Instance-based Penalization Techniques for Classification. In H. Dai, J.N.K. Liu & E. Smirnov (Eds.), Reliable Knowledge Discovery (pp. 227-238). New York: Springer.
  • Porck, J.P., van Knippenberg, D., Tarakci, M., Ates, N.Y., Groenen, P.J.F. & de Haas, M. (2012). Strategic Consensus Between Groups: A Social Identity Perspective. In ERIM Report Series.
  • Borg, I, Groenen, P.J.F., Jehn, K.A., Bilsky, W. & Schwartz, S.H. (2010). Embedding the organizational culture profile into Schwartz's theory of universals in values. Journal of Personnel Psychology, 10 (1), 1-12. doi: http://dx.doi.org/10.1027/1866-5888/a000028[go to publisher's site]
  • Nalbantov, G.I., Franses, P.H.B.F., Groenen, P.J.F. & Bioch, J.C. (2010). Estimating the Market Share Attraction Model using Support Vector Regressions. Econometric Reviews, 29 (5/6), 688-716. doi: http://dx.doi.org/10.1080/07474938.2010.481989[go to publisher's site]
  • Loos, M.J.H.M. van der, Koellinger, P.D., Groenen, P.J.F. & Thurik, A.R. (2010). Genome-wide association studies and the genetics of entrepreneurship. European Journal of Epidemiology, 25 (1), 1-3. doi: http://dx.doi.org/10.1007/s10654-009-9418-8[go to publisher's site]
  • Rosmalen, J.M. van, Koning, A.J. & Groenen, P.J.F. (2010). Optimaal schalen van interactie-effecten. In A.E. Bronner et al., P. Dekker, E. de Leeuw, L.J. Paas, K. de Ruyter, A. Smidts & J.E. Wieringa (Eds.), Ontwikkelingen in het marktonderzoek: Jaarboek 2010 (pp. 177-193). Haarlem: Spaarenhout.
  • Gower, J.C., Groenen, P.J.F. & Velden, M. van de (2010). Area biplots. Journal of Computational and Graphical Statistics, 19 (1), 46-61. doi: http://dx.doi.org/10.1198/jcgs.2010.07134
  • Blasius, J., Greenarcre, M., Groenen, P.J.F. & Velden, M. van de (2009). Special issue on correspondence analysis and related methods. Computational Statistics & Data Analysis, 53, 3103-3106. doi: http://dx.doi.org/10.1016/j.csda.2008.11.010
  • Rosmalen, J.M. van, Groenen, P.J.F., Trejos, J. & Castillo, W. (2009). Optimization strategies for two-mode partitioning. Journal of Classification, 26 (2), 155-181. doi: http://dx.doi.org/10.1007/s00357-009-9031-2
  • Velden, M. van de, Groenen, P.J.F. & Poblome, J. (2009). Seriation by constrained correspondence analysis: A simulation study. Computational Statistics & Data Analysis, 53 (8), 3129-3138. doi: http://dx.doi.org/10.1016/j.csda.2008.08.020
  • Groenen, P.J.F., Hofman, A., Koellinger, P.D., Loos, M.J.H.M. van der, Rivadeneira, F., Rooij, F.J.A. van, Thurik, A.R. & Uitterlinden, A.G. (2008). Genome-wide association for loci influencing entrepreneurial behavior: The Rotterdam Study. Behavior Genetics, 38, 628-629. doi: http://dx.doi.org/10.1007/s10519-008-9228-x
  • Heij, C., Dijk, D.J.C. van & Groenen, P.J.F. (2008). Macroeconomic forecasting with matched principal components. International Journal of Forecasting, 24 (1), 87-100. doi: http://dx.doi.org/10.1016/j.ijforecast.2007.08.005[go to publisher's site]
  • Kagie, M., Wezel, M.C. van & Groenen, P.J.F. (2008). An Online Shopping Interface Based on a Joint Product and Attribute Category Map. In Proceedings of 1st IUI Workshop on Recommendation and Collaboration ReColl 2008.
  • Kagie, M., Wezel, M.C. van & Groenen, P.J.F. (2008). Choosing Attribute Weights for Item Dissimilarity using Clickstream Data with an Application to a Product Catalog Map. In Proceedings of the 2nd ACM International Conference on Recommender Systems (pp. 195-202). New York: ACM Press.
  • Groenen, P.J.F. & Winsberg, S. (2008). 3WaySym-Scal: Three-way symbolic multidimensional scaling. In P. Brito, P. Betrand, G. Cucumel & F. de Carvalho (Eds.), Selected Contributions in Data Analysis and Classification (pp. 55-67). Berlin: Springer.
  • Kagie, M., Groenen, P.J.F. & Wezel, M.C. van (2007). A graphical shopping interface based on product characteristics. In V. Oria, A. Elmagarmid, F. Lochovsky & Y. Saygin (Eds.), Proceedings of the 23rd International Conference on Data Engineering Workshops (pp. 791-800). Los Alamitos, CA: IEEE Computer Society.
  • Geweke, J.F., Groenen, P.J.F., Paap, R. & Dijk, H.K. van (2007). Computational techniques for applied econometric analysis of macroeconomic and financial processes. Computational Statistics & Data Analysis, 51 (7), 3506-3507. doi: http://dx.doi.org/10.1016/j.csda.2006.11.015
  • Heij, C., Groenen, P.J.F. & Dijk, D.J.C. van (2007). Forecast comparison of principal component regression and principal covariate regression. Computational Statistics & Data Analysis, 51 (7), 3612-3625. doi: http://dx.doi.org/10.1016/j.csda.2006.10.019
  • Kagie, M., Wezel, M.C. van & Groenen, P.J.F. (2007). Online shopping using a two dimensional product map. In G. Psaila & R. Wagner (Eds.), E-Commerce and Web Technologies Vol. 4655. Lecture Notes in Computer Science (pp. 89-98). Berlin: Springer.
  • Kagie, M., Wezel, M.C. van & Groenen, P.J.F. (2007). A graphical shopping interface based on product attributes. In M. Somereen, S. Katrenko & P. Adriaans (Eds.), Proceedings of Benelearn 2007 (pp. 45-52). Amsterdam/Netherlands.
  • Groenen, P.J.F., Nalbantov, G.I. & Bioch, J.C. (2007). Nonlinear support vector machines through iterative majorization and I-splines. In R. Decker & H-J. Lenz (Eds.), Advances in Data Analysis, Proceedings of the Geselschaft fur Klassification (pp. 149-162). Berlin: Springer.
  • Linting, M., Meulman, J.J., Groenen, P.J.F. & Kooij, A.J. van der (2007). Nonlinear Principal Components Analysis: Introduction and Application. Psychological Methods, 12 (3), 336-358. doi: http://dx.doi.org/10.1037/1082-989X.12.3.336
  • Linting, M., Meulman, J.J., Groenen, P.J.F. & Kooij, A.J. van der (2007). Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap. Psychological Methods, 12 (3), 359-379. doi: http://dx.doi.org/10.1037/1082-989X.12.3.359
  • Groenen, P.J.F. & Winsburg, S. (2006). Multidimensional scaling of histogram dissimilarities. In V. Batagelj, H.-H. Bock, A. Ferligoj & A. Ziberna (Eds.), Data science and classification (pp. 161-170). Berlin: Springer.
  • Barlow, J.L., Groenen, P.J.F., Park, H. & Zha, H. (2006). 2nd special issue on matrix computations and statistics. Computational Statistics & Data Analysis, 50 (1), 1-4. doi: http://dx.doi.org/10.1016/j.csda.2004.08.003
  • Franses, P.H.B.F., Groenen, P.J.F. & Wagelmans, A.P.M. (2006). Editorial introduction, special issue: 50 years of Econometric Institute and 60 years of Statistica Neerlandica. Statistica Neerlandica, 60 (2), 79-79.
  • Groenen, P.J.F. & Ark, A. van (2006). Visions of 70 years of psychometrics: the past, present, and future. Statistica Neerlandica, 60 (2), 135-144. doi: http://dx.doi.org/10.1111/j.1467-9574.2006.00318.x
  • Nalbantov, G.I., Bioch, J.C. & Groenen, P.J.F. (2006). Classification with support hyperplanes. In J. Furnkranz, T. Scheffer & M. Spiliopoulou (Eds.), MACHINE LEARNING: ECML 2006, PROCEEDINGS Lecture Notes in Computer Science (pp. 703-710). Berlin/Heidelberg: Springer.
  • Groenen, P.J.F. & Koning, A.J. (2006). A new model for visualizing interactions in analysis of variance. In M. Greenacre & J. Blasius (Eds.), Multiple correspondence analysis and related methods. (pp. 487-502). London: Chapman & Hall.
  • Groenen, P.J.F., Winsberg, S., Rodriguez, O. & Diday, E. (2006). I-scal: multidimensional scaling of interval dissimilarities. Computational Statistics & Data Analysis, 51, 360-378. doi: http://dx.doi.org/10.1016/j.csda.2006.04.003
  • Nalbantov, G.I., Bioch, J.C. & Groenen, P.J.F. (2006). Solving and interpreting binary classification problems in marketing with SVMs. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nurnberger & W. Gaul (Eds.), From data and information analysis to knowledge engineering. (pp. 566-573).
  • Kiers, H.A.L. & Groenen, P.J.F. (2006). Visualizing dependence of bootstrap confidence intervals for methods yielding spatial configurations. In S. Zani, A. Cerioli, M. Riani & M. Vichi (Eds.), Data analysis, classification and the forward search. (pp. 119-126). Berlin: Springer.
  • Deun, K. van, Groenen, P.J.F., Heiser, W.J., Busing, F.M.T.A. & Delbeke, L. (2005). Interpreting degenerate solutions in unfolding by use of the vector model and the compensatory distance model. Psychometrika, 70 (1), 45-69. doi: http://dx.doi.org/10.1007/s11336-002-1046-0
  • Groenen, P.J.F. & Velden, M. van de (2005). Multidimensional Scaling. In B.S. Everitt & D.C. Howel (Eds.), Encyclopedia of Statistics in Behavioral Sciences Vol. 2. Encyclopedia of Statistics in Behavioral Sciences (pp. 1280-1289).
  • Groenen, P.J.F., Giaquinto, P. & Kiers, H.A.L. (2005). An improved majorization algorithm for robust procrustes analysis. In M. Vichi, P. Monari, S. Mignani & A. Montanari (Eds.), New Delelopments in Classification and Data Analysis New Developments in Classification and Data Analysis (pp. 151-158). Bologna: Springer-Verlag.
  • Groenen, P.J.F. (2004). Visualisatie met dynamische meerdimensionele schaling. Ontwikkelingen in het Marktonderzoek / Jaarboek MOA, 2004, 183-195.
  • Groenen, P.J.F. & Meulman, J.J. (2004). A comparison of the ratio of variances in distance-based and classical multivariate analysis. Statistica Neerlandica, 58 (4), 428-439. doi: http://dx.doi.org/10.1111/j.1467-9574.2004.00269.x
  • Groenen, P.J.F. & Velden, M. van de (2004). Inverse correspondence analysis. Linear Algebra and its Applications, 388, 221-238. doi: http://dx.doi.org/10.1016/j.laa.2003.10.016
  • Pietersz, R. & Groenen, P.J.F. (2004). Rank reduction of correlation matrices by majorization. Quantitative Finance, 4 (6), 649-662. doi: http://dx.doi.org/10.1080/14697680400016182
  • Velden, M. van de, Groenen, P.J.F. & Poblome, J. (2003). Seriation met bedingter Korrespondenzanalyse: Simulationsexperimente. Archaologische informationen, 26, 449-455.
  • Poblome, J. & Groenen, P.J.F. (2002). Constrained correspondence analysis for seriation of Sagalassos tablewares. In M. Doerr & A. Sarris (Eds.), Proceedings of the 30th Conference : Computer Applications and Quantitative Methods in Archaeology (pp. 90-97). Heraklion, Crete: CAA 2002.
  • Groenen, P.J.F. & Jajuga, K. (2001). Fuzzy clustering with squared Minkowski distances. Fuzzy Sets & Systems, 120 (2), 227-237.
  • Groenen, P.J.F. & Poblome, J. (2001). Constrained correspondence analysis for seriation in archaeology applied to Sagalassos ceramic tablewares. In M. Schwaiger & O. Opitz (Eds.), Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Munich, March 16-16, 2001 - Exploratory Data Analysis in Empirical Research (pp. 301-306). Berlin/ Heidelberg/ New York: Springer-Verlag.
  • Groenen, P.J.F. & Franses, P.H.B.F. (2000). Visualizing time-varying correlations across stock market. Journal of Empirical Finance, 7 (2), 155-172. doi: http://dx.doi.org/10.1016/S0927-5398(00)00009-8
  • Borg, I & Groenen, P.J.F. (2005). Modern multidimensional scaling: Theory and applications (Springer Series in Statistics, 22). New York: Springer.
  • Borg, I, Groenen, P.J.F. & Mair, P. (2013). Applied Multidimensional Scaling (SpringerBriefs in Statistics). Heidelberg: Springer.
  • Borg, I, Groenen, P.J.F. & Mair, P. (2010). Multidimensionele Skaliering (Sozialwissenschaftliche Forschungsmethoden, Band 1). Muenchen: Rainer Hampp Verlag.
  • Groenen, P.J.F. & Borg, I (2015). Multidimensional Scaling II. In JD Wright (Ed.), International Encyclopedia of the Social & Behavioral Sciences (pp. 40-47). Oxford: Elsevier. http://hdl.handle.net/1765/78051
  • Groenen, P.J.F., Kaymak, U. & Rosmalen, J.M. van (2007). Fuzzy clustering with Minkowski distance functions. In J Valente de Oliveira & W Pedrycz (Eds.), Advances in fuzzy clustering and its applications (pp. 53-68). Chicester: Wiley.
  • Groenen, P.J.F. & Koning, A.J. (2005). Generalized bi-additive modelling for categorical data. In M. Vichi, P. Monari, S. Mignani & M. Montanari (Eds.), New development in classification and data analysis (pp. 159-166). Heidelberg: Springer.
  • Tarakci, M., Greer, L.L. & Groenen, P.J.F. (2015). “Leadership Qualities” vs. Competence: Which Matters More? (blog). Harvard Business Review.
  • Loos, M.J.H.M. van der, Groenen, P.J.F., Hofman, A., Koellinger, P.D., Rivadeneira, F., Rooij, F.J.A. van, Thurik, A.R. & Uitterlinden, A.G. (2011). De genetica van ondernemerschap. Economisch-Statistische Berichten, 96 (4609s), 30-36.
  • Pietersz, R. & Groenen, P.J.F. (2004). A major Libor fit. Risk. Currencies, Interest Rates, Equities, 17 (12), 102.
  • Groenen, P.J.F. & Stappers, J. (2003). Dynamische meerdimensionele schaling. Stator, 4 (2), 4-10.
Gertjan van den Burg

Advances in Regularized Methods for Sparse Prediction

Pieter Schoonees

Methods for Modelling Response Styles

Niels Rietveld

Essays on the Intersection of Economics and Biology

Nufer Ates

The Strategy Process: A Middle Management Perspective

  • Role: Promotor
  • PhD Candidate: Nufer Ates
  • Time frame: 2009 - 2014
Murat Tarakci

Behavioral Strategy: Strategic Consensus, Power and Networks

Editorial positions

  • Statistica Neerlandica

    Associate Editor

  • Psychometrika

    Associate Editor

  • Associate Editor

  • Advances in Data Analysis and Classification

    Associate Editor

Past courses

Integrating genetics into economics

Due to recent and spectacular breakthroughs in genetics research, the future of economics will be heavily influenced by insights into genetic determinants of behaviour and life outcomes. Erasmus University Rotterdam is at the forefront of these new developments. In this PhD project, the candidate will take the next step attempting to integrate genetic insights into economics.

First, the candidate will analyse to which extent different socio-economic behaviours and outcomes can be explained using genetic factors, and whether they are related on the genetic level. Next, the candidate will include genetic factors in existing economic models to analyse the value added for economists of taking into account genetic differences between individuals. Lastly, the candidate will attempt to use genetic variants as instrumental variables in existing economic models to infer causality.

The candidate will work with data from many different sources, such as the Health and Retirement Study, the Rotterdam Study and the UK Biobank. The outcome of the project will consist in a number of research papers that will form the contents of the PhD dissertation.

The candidate will become a member of EURIBEB, the Erasmus University Rotterdam Institute for Biology and Economic Behaviour (http://www.euribeb.nl).

EURIBEB conducts interdisciplinary and collaborative research on the intersection of biology and (economic) behaviour. Its research has been published in high-impact journals such as Science, Nature and PNAS. EURIBEB has prominent affiliated researchers from different EUR faculties (such as Economics, Erasmus MC and Social Sciences) and other universities (such as the Vrije Universiteit Amsterdam, Stockholm School of Economics, and University of Southern California).

Candidates should have a recently/almost completed Master’s degree in economics, econometrics, behavioural genetics, epidemiology, or another field that provides a sufficient background in statistics. Good computer skills and knowledge of programming languages are an advantage. Furthermore, curiosity and an interest to work in an interdisciplinary environment are regarded as assets. The necessary skills for using the appropriate statistical methods can be learned during the first year of employment.

It is possible for current MSc students of the Erasmus School of Economics to write a Master’s thesis on this topic prior to employment as PhD student.

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What characterizes the entrepreneur? On the neurocognition of economic behavior.

Recent years witnessed a huge increase in our knowledge of the neurocognitive mechanisms of deviant and psychopathological behavior. This increase in knowledge can be applied extensively in analyzing individuals’ economic behavior. In this project, two PhD positions are available. They provide a unique opportunity to be among the first researchers working in the interdisciplinary field of economics, neurobiology, and clinical psychology, using novel approaches for modelling economic behavior.

The project aims to advance our fundamental knowledge about economic behavior, particularly entrepreneurship, using determinants originally developed to assess symptoms derived from the field of clinical and neuropsychology. This approach taken in this project will develop our understanding and improve the prediction of (successful) entrepreneurial behavior. Other types of economic behavior and outcomes such as unemployment, education, health, and happiness will be studied following a similar approach. The candidates will be free to develop several models, where economic behavior is the starting point and neurobiological measures and/or psychiatric symptoms are determinants, from an overall model. The candidates will be given the opportunity to collect their own (EEG) data set for measuring brain activity in a variety of relevant contexts.

Both projects are approved by EUR’s Research Excellence Initiative (REI). The aim of the research excellence initiative is to enhance the quality and impact of EUR research, stimulate collaboration between disciplines, thus to attract top talent to the EUR, and to reach higher visibility for the best research groups on the international scale. The outcome of the projects will consist in a number of research papers that will form the contents of the PhD dissertations.

Besides, the candidate will become a member of EURIBEB, the Erasmus University Rotterdam Institute for Biology and Economic Behavior (http://www.euribeb.nl). EURIBEB conducts interdisciplinary and collaborative research on the intersection of biology and (economic) behavior. Its research has been published in high-impact journals such as Science, Nature and PNAS. EURIBEB has prominent affiliated researchers from different EUR faculties (such as Economics, Erasmus MC and Social Sciences) and other universities (such as the Vrije Universiteit Amsterdam, Stockholm School of Economics, and University of Southern California).

Candidates should have a recent or almost completed Master’s degree in economics, econometrics, behavioral genetics, epidemiology, or another field that provides a sufficient background in statistics. Good computer skills and knowledge of programming languages are an advantage. Furthermore, curiosity and an interest to work in an interdisciplinary environment are regarded as assets. The necessary skills for using the appropriate statistical methods can be learned during the first year of employment.

It is possible for current MSc students of the Erasmus School of Economics to write a Master’s thesis on this topic prior to employment as PhD student.

The two PhD candidates will be part of larger interdisciplinary team of internationally recognized researchers that includes three other PhDs.

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Open PhD project at the Econometric Institute

The Econometric Institute is one of the leading research groups in econometrics in Europe. The group has an opening for a PhD student with an interest in one of the following four broad application areas:

  • Macroeconometrics
  • Financial econometrics/quantitative finance
  • Microeconometrics with applications in economics, marketing or business analytics .
  • Statistics, multivariate analysis, computational statistics, and visuzalization.

The exact topic of the PhD project will be decided upon in coordination with the candidate. Promotores are either Dennis Fok, Patrick Groenen, Richard Paap and/or Dick van Dijk depending on the preferred topic.

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Address

Visiting address

Office: Tinbergen Building H11-11
Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam
Netherlands

Work in progress

Heij, C., Exterkate, P., Groenen, P.J.F. & Dijk, D.J.C. van (2016). Nonlinear forecasting with many predictors using kernel ridge regression. International Journal of Forecasting, To appear.
Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, JJ, Pers, TH, Rietveld, C.A., Turley, P, Chen, G-B, Emilsson, V, Meddens, S.F.W., Oskarsson, S, Pickrell, J.K., Thom, K, Timshel, P, Vlaming, R. de, Lee, S.J. van der, Amin, N., Rooij, F.J.A. van, Duijn, C.M. van, Groenen, P.J.F., Thurik, A.R., Tiemeier, H.W., Uitterlinden, A.G., Hofman, A., SSGAC, The, Yang, J., Johannesson, M., Visscher, P.M., Esko, T, Koellinger, P.D., Cesarini, D.A. & Benjamin, D.J. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, Under rev..

Latest publication

Tarakci, M., Greer, L.L. & Groenen, P.J.F. (2016). When does power disparity help or hurt group performance? Journal of Applied Psychology, Accepted. doi: http://dx.doi.org/10.1037/apl0000056