P.J.F. (Patrick) Groenen

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

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.

Work in Progress (3)

Publications (92)

Key Publications (15)

Articles (81)

  • Tenenhaus, M., Tenenhaus, A. & Groenen, P.J.F. (2017). Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods. Psychometrika. doi: 10.1007/s11336-017-9573-x
  • Vlaming, R. de, Okbay, A., Rietveld, C.A., Johannesson, M, Magnusson, PKE, Uitterlinden, A.G., Rooij, F.J.A. van, Hofman, A., Groenen, P.J.F., Thurik, R. & Koellinger, P.D. (2017). Meta-GWAS Accuracy and Power (MetaGAP) calculator shows that hiding heritability is partially due to imperfect genetic correlations across studies. PLoS Genetics (online), 13 (1):e1006495. doi: 10.1371/journal.pgen.1006495
  • Groenen, P.J.F. & Velden, M. van de (2016). Multidimensional Scaling by Majorization: A Review. Journal of Statistical Software, 73 (8), 1-26. doi: http://dx.doi.org/10.18637/jss.v073.i08
  • Tarakci, M., Greer, L.L. & Groenen, P.J.F. (2016). When does power disparity help or hurt group performance? Journal of Applied Psychology, 101 (3), 415-429. doi: http://dx.doi.org/10.1037/apl0000056
  • Burg, G.J.J. van den & Groenen, P.J.F. (2016). GenSVM: A Generalized Multiclass Support Vector Machine. Journal of Machine Learning Research, 17 (225), 1-42. doi: http://jmlr.org/papers/v17/14-526.html
  • Barban, N., Jansen, R., Vlaming, R. de, Vaez, A, Mandemakers, J.J., Tropf, F.C., Shen, X, Wilson, JF, Chasman, DI, Nolte, I.M., Tragante, V, Laan, S.W. van der, Perry, JRB, Kong, A, Ahluwalia, TS, Albrecht, E, Yerges-Armstrong, L, Atzmon, G, Auro, K, Ayers, K, Bakshi, A, Ben-Avraham, D, Berger, K., Bergman, A., Bertram, L, Bielak, LF, Bjornsdottir, G, Bonder, MJ, Broer, L., Bui, M, Barbieri, C, Cavadino, A, Chavarro, JE, Turman, C, Concas, MP, Cordell, HJ, Davies, G., Eibich, P, Eriksson, N, Esko, T, Eriksson, J, Falahi, F, Felix, J.F., Fontana, M.A., Franke, L, Gandin, I, Gaskins, AJ, Gieger, C, Gunderson, EP, Guo, XQ, Hayward, C, He, CY, Hofer, E, Huang, HY, Joshi, PK, Kanoni, S, Karlsson, R, Kiechl, S, Kifley, A, Kluttig, A., Kraft, P, Lagou, V, Lecoeur, C, Lahti, J, Li-Gao, RF, Lind, PA, Liu, T., Makalic, E, Mamasoula, C, Matteson, L, Mbarek, H, McArdle, PF, McMahon, G, Meddens, SFW, Mihailov, E, Miller, M, Missmer, SA, Monnereau, C., Most, PJ van der, Myhre, R, Nalls, MA, Nutile, T, Kalafati, IP, Porcu, E, Prokopenko, I, Rajan, KB, Rich-Edwards, J, Rietveld, C.A., Robino, A, Rose, LM, Rueedi, R, Ryan, KA, Saba, Y, Schmidt, D., Smith, JA, Stolk, L., Streeten, E, Tonjes, A, Thorleifsson, G, Ulivi, S, Wedenoja, J, Wellmann, J, Willeit, P, Yao, J, Yengo, L, Zhao, JH, Zhao, W, Zhernakova, DV, Amin, N., Andrews, H, Balkau, B, Barzilai, N, Bergmann, S, Biino, G, Bisgaard, H, Bonnelykke, K, Boomsma, D.I., Buring, JE, Campbell, H, Cappellani, S, Ciullo, M, Cox, SR, Cucca, F, Toniolo, D., Davey-Smith, G, Deary, IJ, Dedoussis, G, Deloukas, P, Duijn, C.M. van, Geus, E.J.C. de, Eriksson, JG, Evans, DA, Faul, JD, Sala, CF, Froguel, P, Gasparini, P, Girotto, G, Grabe, HJ, Greiser, K.H., Groenen, P.J.F., Haan, HG de, Haerting, J, Harris, T.B., Heath, AC, Heikkila, K, Hofman, A., Homuth, G., Holliday, EG, Hopper, J, Hypponen, E, Jacobsson, B, Jaddoe, V.W.V.K., Johannesson, M, Kahonen, M, Kajantie, E, Kardia, SLR, Keavney, B., Kolcic, I, Koponen, P, Kovacs, P, Kronenberg, F, Kutalik, Z, Bianca, M La, Lachance, G, Iacono, WG, Lai, S, Lehtimaki, T, Liewald, DC, Lindgren, CM, Liu, YM, Luben, R, Lucht, M, Luoto, R, Magnus, P, Magnusson, PKE, Martin, NG, McGue, M, McQuillan, R, Medland, SE, Meisinger, C, Mellstrom, D., Metspalu, A, Traglia, M, Milani, L, Mitchell, P., Montgomery, GW, Mook-Kanamori, D, Mutsert, R de, Nohr, EA, Ohlsson, C, Olsen, P, Ong, KK, Paternoster, L, Pattie, A, Penninx, BWJH, Perola, M, Peyser, PA, Pirastu, M, Polasek, O, Power, C, Kaprio, J, Raffel, LJ, Raikkonen, K, Raitakari, O, Ridker, P.M., Ring, SM, Roll, K, Rudan, I, Ruggiero, D, Rujescu, D, Salomaa, V, Schlessinger, D, Schmidt, H., Schmidt, R., Schupf, N, Smit, J., Sorice, R, Spector, T.D., Starr, JM, Stockl, D, Strauch, K, Stumvoll, M., Swertz, MA, Thorsteinsdottir, U, Thurik, AR, Timpson, NJ, Tung, JY, Uitterlinden, A.G., Vaccargiu, S, Viikari, J, Vitart, V, Volzke, H, Vollenweider, P, Vuckovic, D, Waage, J, Wagner, GG, Wang, J.J., Wareham, NJ, Weir, DR, Willemsen, G, Willeit, J, Wright, AF, Zondervan, KT, Stefansson, K, Krueger, RF, Lee, JJ, Benjamin, D.J., Cesarini, D., Koellinger, PD, Hoed, M den, Snieder, H & Mills, M.C. (2016). Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nature Genetics, 48 (12), 1462-1472. doi: http://dx.doi.org/10.1038/ng.3698[go to publisher's site]
  • Exterkate, P., Groenen, P.J.F., Heij, C. & Dijk, D.J.C. van (2016). Nonlinear forecasting with many predictors using kernel ridge regression. International Journal of Forecasting, 32 (3), 736-753. doi: http://dx.doi.org/10.1016/j.ijforecast.2015.11.017
  • Greenacre, Michael J. & Groenen, P.J.F. (2016). Weighted Euclidean Biplots. Journal of Classification, 33, 442-459. doi: 10.1007/s00357-016-9213-7
  • Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, JJ, Pers, TH, Rietveld, C.A., Turley, P, Chen, GB, Emilsson, V, Meddens, SFW, Oskarsson, S, Pickrell, J.K., Thom, K, Timshel, P, Vlaming, R. de, Abdellaoui, A, Ahluwalia, TS, Bacelis, J, Baumbach, C, Bjornsdottir, G, Brandsma, J.H., Concas, MP, Derringer, J, Furlotte, NA, Galesloot, TE, Girotto, G, Gupta, R., Hall, LM, Harris, SE, Hofer, E, Horikoshi, M, Huffman, JE, Kaasik, K, Kalafati, IP, Karlsson, R, Kong, A, Lahti, J, Lee, S.J. van der, Leeuw, C. de, Lind, PA, Lindgren, KO, Liu, T., Mangino, M, Marten, J, Mihailov, E, Miller, MB, Most, PJ van der, Oldmeadow, C, Payton, A, Pervjakova, N, Peyrot, WJ, Qian, Y., Raitakari, O, Rueedi, R, Salvi, E, Schmidt, B., Schraut, KE, Shi, JX, Smith, AV, Poot, R.A., Pourcain, B St, Teumer, A, Thorleifsson, G, Verweij, N., Vuckovic, D, Wellmann, J, Westra, HJ, Yang, JY, Zhao, W, Zhu, ZH, Alizadeh, B.Z., Amin, N., Bakshi, A, Baumeister, SE, Biino, G, Bonnelykke, K, Boyle, PA, Campbell, H, Cappuccio, F.P., Davies, G., Neve, JE De, Deloukas, P, Demuth, I, Ding, J, Eibich, P, Eisele, L, Eklund, N, Evans, DM, Faul, JD, Feitosa, MF, Forstner, AJ, Gandin, I, Gunnarsson, B, Halldorsson, BV, Harris, T.B., Heath, AC, Hocking, LJ, Holliday, EG, Homuth, G., Horan, MA, Hottenga, JJ, Jager, PL De, Joshi, PK, Jugessur, A, Kaakinen, MA, Kahonen, M, Kanoni, S, Keltigangas-Jarvinen, L, Kiemeney, L.A.L.M., Kolcic, I, Koskinen, S, Kraja, AT, Kroh, M, Kutalik, Z, Latvala, A, Launer, LJ, Lebreton, MP, Levinson, DF, Lichtenstein, P., Lichtner, P, Liewald, DCM, Loukola, A, Madden, PA, Magi, R, Maki-Opas, T, Marioni, RE, Marques-Vidal, P, Meddens, GA, McMahon, G, Meisinger, C, Meitinger, T, Milaneschi, Y, Milani, L, Montgomery, GW, Myhre, R, Nelson, CP, Nyholt, DR, Ollier, WER, Palotie, A, Paternoster, L, Pedersen, NL, Petrovic, KE, Porteous, D.J., Raikkonen, K, Ring, SM, Robino, A, Rostapshova, O, Rudan, I, Rustichini, A, Salomaa, V, Sanders, AR, Sarin, AP, Schmidt, H., Scott, R.J., Smith, BH, Smith, JA, Staessen, JA, Steinhagen-Thiessen, E, Strauch, K, Terracciano, A, Tobin, MD, Ulivi, S, Vaccargiu, S, Quaye, L, Rooij, F.J.A. van, Venturini, C, Vinkhuyzen, AAE, Volker, U, Volzke, H, Vonk, JM, Vozzi, D, Waage, J, Ware, EB, Willemsen, G, Attia, JR, Bennett, DA, Berger, K., Bertram, L, Bisgaard, H, Boomsma, D.I., Borecki, IB, Bultmann, U, Chabris, C.F., Cucca, F, Cusi, D, Deary, IJ, Dedoussis, GV, Duijn, C.M. van, Eriksson, JG, Franke, B., Franke, L, Gasparini, P, Gejman, PV, Gieger, C, Grabe, HJ, Gratten, J, Groenen, P.J.F., Gudnason, V, Harst, P. van der, Hayward, C, Hinds, DA, Hoffmann, W., Hyppnen, E, Iacono, WG, Jacobsson, B, Jarvelin, MR, Jockel, KH, Kaprio, J, Kardia, SLR, Lehtimaki, T, Lehrer, SF, Magnusson, PKE, Martin, NG, McGue, M, Metspalu, A, Pendleton, N, Penninx, BWJH, Perola, M, Pirastu, N, Pirastu, M, Polasek, O, Posthuma, D., Power, C, Province, MA, Samani, NJ, Schlessinger, D, Schmidt, R., Sorensen, T.I.A., Spector, T.D., Stefansson, K, Thorsteinsdottir, U, Thurik, A.R., Timpson, NJ, Tiemeier, H.W., Tung, JY, Uitterlinden, A.G., Vitart, V, Vollenweider, P, Weir, DR, Wilson, JF, Wright, AF, Conley, DC, Krueger, RF, Smith, G.D., Hofman, A., Laibson, D.I., Medland, SE, Meyer, MN, Yang, J., Johannesson, M, Visscher, P.M., Esko, T, Koellinger, P.D., Cesarini, D. & Benjamin, D.J. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533 (7604), 539-542. doi: http://dx.doi.org/10.1038/nature17671
  • Vlaming, R. de & Groenen, P.J.F. (2015). The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics. BIOMED RESEARCH INTERNATIONAL. doi: 10.1155/2015/143712
  • 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[go to publisher's site]
  • 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]
  • 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
  • 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., 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]
  • 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
  • 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]
  • 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]
  • 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]
  • 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]
  • 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.
  • 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.
  • 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]
  • 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.
  • 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]
  • 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. doi: 10.1787/jbcma-2011-5kgdwlpzs79v[go to publisher's site]
  • 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]
  • 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.
  • 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]
  • 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]
  • 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
  • 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, 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]
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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., 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.
  • 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.
  • 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]
  • 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
  • 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.
  • 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
  • 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.
  • 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., 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.
  • 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
  • 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.
  • 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
  • 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).
  • 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.
  • 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.
  • 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.
  • 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., 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
  • 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.
  • 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
  • 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
  • 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]
  • 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
  • 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
  • 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

Books (3)

  • 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.
  • Borg, I & Groenen, P.J.F. (2005). Modern multidimensional scaling: Theory and applications (Springer Series in Statistics, 22). New York: Springer.

Book Contributions (3)

  • 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.
  • 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.

Inaugural Speech

Professional Publications (4)

  • 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.

PhD Projects (18)

Psychiatric symptoms and decision making across the life span of the general

Eric Slob

Integrating genetics into economics

  • Role: Promotor
  • PhD Candidate: Eric Slob
  • Time frame: 2016 -
Yik Kiu (Plato) Leung

Entrepreneurship and mental health

Indy Bernoster

Economic behaviour, in particular entrepreneurship, and reward sensitivity

Aysu Okbay

Essays on Genetics and the Social Sciences

  • Role: Promotor
  • PhD Candidate: Aysu Okbay
  • Time frame: 2012 - 2017
Ronald de Vlaming

Linear Mixed Models in Statistical Genetics

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
Jeanine Porck

No Team is an Island: an Integrative View of Strategic Consensus between Groups

Matthijs van der Loos

Molecular Genetics and Hormones: New Frontiers in Entrepreneurship Research

Murat Tarakci

Behavioral Strategy: Strategic Consensus, Power and Networks

Peter van der Zwan

The Entrepreneurial Process: An International Analysis of Entry and Exit

Martijn Kagie

Advances in Online Shopping Interfaces: Product Catalog Maps and Recommender Systems

Joost van Rosmalen

Segmentation and Dimension Reduction: Exploratory and Model-Based Approaches

Georgi Nalbantov

Essays on Some Recent Penalization Methods with Applications in Finance and Marketing

Danielle van Hout

Measuring Meaningful Differences: Sensory testing based decision making in an industrial context; applications of signal detection theory and Thurstonian modelling

Recognitions (5)

Editorial positions

  • Statistica Neerlandica

    Associate Editor

  • Psychometrika

    Associate Editor

  • Associate Editor

  • Advances in Data Analysis and Classification

    Associate Editor

  • Journal of Statistical Software

    Associate Editor

Courses (6)

Past courses

PhD Vacancies (1)

Data science for the public sector

This project focuses on developing and applying novel, non-parametric, methods to explore large data sets. In particular, we aim to develop methods that can be used both to summarize relationships and, if appropriate, predict relevant events. The focus will be on new, algorithmic approaches that require no distributional assumptions and their application to applications in the public sector.

Some specific problems often encountered in “big data” related prediction and exploration settings that are to be addressed in this study concern:

  • Sample selection and balance problems (e.g., many prediction problems concern relatively “rare” events. In such cases, often non-random samples are taken and used as input for prediction models);
  • Automated variable selection procedures (e.g., which variables, or combinations thereof, are relevant for predicting and/or understanding, certain events);
  • Time dependence and dynamics of the problems (i.e., with quickly changing environments, models need to be updated frequently or even continuously. However, many advanced prediction methods are computationally intensive making it impossible to provide fast, and accurate, results);
  • Interpretation of results. Machine learning methods place a heavy emphasis on prediction performance. Consequently, interpretation of the results is often not trivial. Applications in the public sector, however, can have far reaching societal impact. Therefore, understanding of the roles of leading indicators and/or underlying interactions, is of great importance.
Read more

Events (8)

2014
November
20
ERIM Seminar on Professionalism and Integrity
ERIM Research Seminar
2014
November
04
ERIM Seminar on Professionalism and Integrity
ERIM Research Seminar
2009
June
10
Joint ERIM-Unipark Symposium on Online Research: Insights Into Methods and their Application in Practice
ERIM Institute Event
2009
April
23
Efficient Experimental Designs for Choice-Based Conjoint Analysis
ERIM Research Seminar
2009
April
21
Modeling Geo-dependent Attitudes Using Bayesian Spatial Factor Analysis
ERIM Research Seminar
2008
September
12
Introduction and Developments on Support Vector Machines and Classification
ERIM Research Workshop
2007
June
25
CARME 2007 Conference
Conference
2005
March
21
Visualizing Consumers' Preference for Products by Ordinal Unfolding using PrefScal
ERIM Research Seminar

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

Slob, E.A.W., Groenen, P.J.F., Thurik, A.R. & Rietveld, C.A. (2017). A Note on the Use of Egger Regression in Mendelian Randomization Studies. International Journal of Epidemiology.
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.

Latest publication

Vlaming, R. de, Okbay, A., Rietveld, C.A., Johannesson, M, Magnusson, PKE, Uitterlinden, A.G., Rooij, F.J.A. van, Hofman, A., Groenen, P.J.F., Thurik, R. & Koellinger, P.D. (2017). Meta-GWAS Accuracy and Power (MetaGAP) calculator shows that hiding heritability is partially due to imperfect genetic correlations across studies. PLoS Genetics (online), 13 (1):e1006495. doi: 10.1371/journal.pgen.1006495