Dr. M. (Michel) van de Velden

Michel van de Velden
Erasmus School of Economics (ESE)
Erasmus University Rotterdam
Member ERIM
Field: Marketing
Affiliated since 2004

Michel van de Velden is an associate Professor of Statistics at the Econometric Institute of the Erasmus University Rotterdam. His main research interests are exploratory data analysis. In particular,  dimension reduction and cluster analysis methods with a strong focus on data visualization. In addition, he is in involved in several supervised machine learning projects involving tree-based machine learning methods.

Publications

Article (46)

  • Academic (44)

    • Willemsen, R. S. H., van de Velden, M., & van den Heuvel, W. (2024). On the uniqueness of correspondence analysis solutions. Linear Algebra and Its Applications, 690, 162-185. https://doi.org/10.1016/j.laa.2024.03.014

    • van de Velden, M., D’Enza, A. I., Markos, A., & Cavicchia, C. (2024). A general framework for implementing distances for categorical variables. Pattern Recognition, 153, Article 110547. https://doi.org/10.1016/j.patcog.2024.110547

    • Willemsen, R. S. H., van den Heuvel, W., & van de Velden, M. (2023). A new mixed integer programming approach for inverse correspondence analysis. Computers and Operations Research, 160, Article 106375. https://doi.org/10.1016/j.cor.2023.106375

    • Torres, A., de Carvalho, L. V., Machado, J. C., van de Velden, M., & Costa, P. (2023). Exploring consumer segments defined by affective responses to naturalness in logo design. Journal of Product and Brand Management, 32(8), 1287-1305. https://doi.org/10.1108/JPBM-06-2022-4023

    • Lombardo, R., van de Velden, M., & Beh, E. J. (2023). Three-Way Correspondence Analysis in R. R Journal, 15(2), 237-262. https://doi.org/10.32614/RJ-2023-049

    • Knapp, S., & van de Velden, M. (2023). Exploration of machine learning methods for maritime risk predictions. Maritime Policy and Management, 51(7), 1443-1473. https://doi.org/10.1080/03088839.2023.2209788

    • Takagishi, M., & Velden, M. V. D. (2022). Visualizing Class Specific Heterogeneous Tendencies in Categorical Data. Journal of Computational and Graphical Statistics, 31(3), 790-801. https://doi.org/10.1080/10618600.2022.2035737

    • Schoonees, P. C., Groenen, P. J. F., & van de Velden, M. (2021). Least-squares bilinear clustering of three-way data. Advances in Data Analysis and Classification, 1001-1037. Advance online publication. https://doi.org/10.1007/s11634-021-00475-2

    • van de Velden, M., van den Heuvel, W., Groenen, P., & Galy, H. (2019). Retrieving a contingency table from a correspondence analysis solution. European Journal of Operational Research, 283(2), 541-548. https://doi.org/10.1016/j.ejor.2019.11.014

    • Takagishi, M., van de Velden, M., & Yadohisa, H. (2019). Clustering preference data in the presence of response?style bias. British Journal of Mathematical and Statistical Psychology, 72, 401-425. https://doi.org/10.1111/bmsp.12170

    • Bransen, L., Haaren, J., & van de Velden, M. (2019). Measuring soccer players’ contributions to chance creation by valuing their passes. Journal of Quantitative Analysis in Sports, 15(2). https://doi.org/10.1515/jqas-2018-0020

    • Markos, A., Iodice D'Enza, A., & van de Velden, M. (2019). Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R. Journal of Statistical Software, 91(10). https://doi.org/10.18637/jss.v091.i10

    • Lorenzo-Seva, U., & van de Velden, M. (2019). MultipleCar: A Graphical User Interface MATLAB Toolbox to Compute Multiple Correspondence Analysis. Journal of Statistical Software, 90(4). https://doi.org/10.18637/jss.v090.i04

    • Torres, A., César Machado, J., Vacas de Carvalho, L., van de Velden, M., & Costa, P. (2019). Same design, same response? Investigating natural designs in international logos. The Journal of Product and Brand Management, 28(3), 317-329. https://doi.org/10.1108/JPBM-10-2017-1632

    • van de Velden, M., Iodice D'Enza, A., & Yamamoto, M. (2019). Special feature: dimension reduction and cluster analysis. Behaviormetrika, 46(2), 239-241. https://doi.org/10.1007/s41237-019-00092-6

    • van de Velden, M., Iodice D'Enza, A., & Markos, A. (2018). Distance-based clustering of mixed data. Wiley Interdisciplinary Reviews. Computational Statistics. https://doi.org/10.1002/wics.1456

    • van de Velden, M., Iodice D'Enza, A., & Palumbo, F. (2016). cluster correspondence analysis. Psychometrika, 82(1), 158-185. https://doi.org/10.1007/s11336-016-9514-0

    • Groenen, P., & van de Velden, M. (2016). Multidimensional Scaling by Majorization: A Review. Journal of Statistical Software, 73(8), 1-26. https://doi.org/10.18637/jss.v073.i08

    • Schoonees, P., van de Velden, M., & Groenen, P. (2015). Constrained Dual Scaling for Detecting Response Styles in Categorical Data. Psychometrika, 80(4), 968-994. https://doi.org/10.1007/s11336-015-9458-9

    • van Dam, J.-W., & van de Velden, M. (2015). Online profiling and clustering of Facebook users. Decision Support Systems, 70, 60-72. https://doi.org/10.1016/j.dss.2014.12.001

    • Gower, JC., Groenen, P., van de Velden, M., & Vines, K. (2014). Better perceptual maps: Introducing explanatory icons to facilitate interpretation. Food Quality and Preference, 36, 61-69. https://doi.org/10.1016/j.foodqual.2014.01.004

    • van de Velden, M., de Beuckelaer, A., Groenen, P., & Busing, FMTA. (2013). Solving degeneracy and stability in nonmetric unfolding. Food Quality and Preference, 27(1), 85-95. https://doi.org/10.1016/j.foodqual.2012.06.010

    • Kim, I.-A., Kim, M.-A., van de Velden, M., & Lee, H.-S. (2013). Psychological positioning of bottled tea products: A comparison between two Kansei profiling techniques. Food Science and Biotechnology, 22(1), 257-268. https://doi.org/10.1007/s10068-013-0035-7

    • Bijmolt, THA., & van de Velden, M. (2012). Multi-attribute perceptual mapping using idiosyncratic brand and attribute sets. Marketing Letters, 23(3), 585-601. https://doi.org/10.1007/s11002-012-9163-8

    • van de Velden, M., & Takane, Y. (2011). Generalized canonical correlation analysis with missing values. Computational Statistics, 27(3), 551-571. https://doi.org/10.1007/s00180-011-0276-y

    • Knapp, S., & van de Velden, M. (2011). Global ship risk profiles: Safety and the marine environment. Transportation Research. Part D, Transport and Environment, 16(8), 595-560. https://doi.org/10.1016/j.trd.2011.08.001

    • Gower, JC., Groenen, P., & van de Velden, M. (2010). Area biplots. Journal of Computational and Graphical Statistics, 19(1), 46-61. https://doi.org/10.1198/jcgs.2010.07134

    • Blasius, J., Greenarcre, M., Groenen, P., & van de Velden, M. (2009). Special issue on correspondence analysis and related methods. Computational Statistics & Data Analysis, 53(8), 3103-3106. https://doi.org/10.1016/j.csda.2008.11.010

    • van de Velden, M., Groenen, P., & Poblome, J. (2009). Seriation by constrained correspondence analysis: A simulation study. Computational Statistics & Data Analysis, 53(8), 3129-3138. https://doi.org/10.1016/j.csda.2008.08.020

    • Lorenzo-Seva, U., van de Velden, M., & Kiers, HAL. (2009). Oblique rotation in correspondence analysis: A step forward in the search for the simplest interpretation. British Journal of Mathematical and Statistical Psychology, 62, 583-600. https://doi.org/10.1348/000711008X368295

    • Lorenzo-Seva, U., van de Velden, M., & Kiers, HAL. (2009). CAR: A MATLAB Package to Compute Correspondence Analysis with Rotations. Journal of Statistical Software, 31(8), 1-14. https://doi.org/10.18637/jss.v031.i08

    • Knapp, S., & van de Velden, M. (2009). Visualization of Differences in Treatment of Safety Inspections across Port State Control Regimes: A Case for Increased Harmonization Efforts. Transport Reviews, 29(4), 499-514. https://doi.org/10.1080/01441640802573749

    • Blasius, J., Greenacre, M., Groenen, P., & Van de Velden, M. (2008). CARME-N — Correspondence Analysis and Related Methods Network CARME 2007. Bulletin de Méthodologie Sociologique, 99(1), 73-81. https://doi.org/10.1177/075910630809900106

    • Torres, A., & van de Velden, M. (2007). Perceptual mapping of multiple variable batteries by plotting supplementary variables in correspondence analysis of rating data. Food Quality and Preference, 18(1), 121-129. https://doi.org/10.1016/j.foodqual.2005.09.005

    • van Herk, H., & van de Velden, M. (2007). Insight into the relative merits of rating and ranking in a cross-national context using three-way correspondence analysis. Food Quality and Preference, 18(8), 1096-1105. https://doi.org/10.1016/j.foodqual.2007.05.006

    • van de Velden, M., & Bijmolt, THA. (2006). Generalized canonical correlation analysis of matrices with missing rows: a simulation study. Psychometrika, 71, 323-331. https://doi.org/10.1007/s11336-004-1168-9

    • Neudecker, H., & van de Velden, M. (2005). Problem section. Statistical Papers, 46(3), 469-472. https://doi.org/10.1007/BF02762846

    • van de Velden, M., & Bijmolt, THA. (2005). A Visualization of the Dutch political landscape using generalized canonical correlation analysis. Medium Econometrische Toepassingen, 13(2), 20-24.

    • van de Velden, M., & Kiers, HAL. (2005). Rotation in Correspondence Analysis. Journal of Classification, 22, 251-271. https://doi.org/10.1007/s00357-005-0016-5

    • Groenen, P., & van de Velden, M. (2004). Inverse correspondence analysis. Linear Algebra and Its Applications, 388, 221-238. https://doi.org/10.1016/j.laa.2003.10.016

    • van de Velden, M. (2004). Optimal scaling of paired comparison data. Journal of Classification, 21, 89-109.

    • van de Velden, M., Groenen, P., & Poblome, J. (2003). Seriation met bedingter Korrespondenzanalyse: Simulationsexperimente. Archaologische informationen, 26, 449-455.

    • van de Velden, M., & Neudecker, H. (2000). On an eigenvalue property relevant in correspondence analysis and related methods. Linear Algebra and Its Applications, 321, 347-364.

    • Neudecker, H., Satorra, A., & Van de Velden, M. (1997). A Fundamental Matrix Result on Scaling in Multivariate Analysis. Econometric Theory, 13(6), 890. https://doi.org/10.1017/S0266466600006332

  • Professional (2)

    • Groot, LFM., & van de Velden, M. (2010). De WK-poulewijzer. Economisch-Statistische Berichten, 95, 362-364.

    • Karsemeijer, B., Franses, P. H., & van de Velden, M. (2007). Saaie Winkelstraten. Economisch-Statistische Berichten, (14 december 2007), 746.

Chapter (2)

  • Academic (2)

    • Iodice D'Enza, A., Groenen, P., & van de Velden, M. (2020). PowerCA: A Fast Iterative Implementation of Correspondence Analysis. In T. Imaizumi, A. Nakayama, & S. Yokoyama (Eds.), Advanced Studies in Behaviormetrics and Data Science (pp. 283-296). Springer-Verlag. https://doi.org/10.1007/978-981-15-2700-5

    • van de Velden, M. (2000). Dual scaling and correspondence analysis of rank order data. In R. D. H. Heijmans, D. S. G. Pollock, & A. Satorra (Eds.), Innovations in Multivariate Statistical Analysis. A Festschrift for Heinz Neudecker (pp. 87-99). Kluwer Academic.

Conference proceeding (4)

  • Academic (4)

    • Iodice D’Enza, A., de Velden, M. V., & Palumbo, F. (2014). On joint dimension reduction and clustering of categorical data. In A. Okada, C. Weihs, D. Vicari, & G. Ragozini (Eds.), Analysis and Modeling of Complex Data in Behavioral and Social Sciences (pp. 161-169). NEI/Kluwer Academic Publishers. https://doi.org/10.1007/978-3-319-06692-9_18

    • van de Velden, M. (2008). Detecting Response Styles by using Dual Scaling of Successive Categories. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.), New trends in psychometrics (pp. 517-524). universal academy press.

    • Groenen, P., & van de Velden, M. (2005). Multidimensional Scaling. In B. S. Everitt, & D. C. Howel (Eds.), Encyclopedia of Statistics in Behavioral Sciences (Vol. 2, pp. 1280-1289)

    • van de Velden, M., & Kiers, HAL. (2001). An application of rotation in correspondence analysis. In H. Yanai, A. Okada, K. Shigemasu, Y. Kano, & J. J. Meulman (Eds.), New Developments in Psychometrics (pp. 471-478). Springer-Verlag.

Preprint (1)

  • Academic (1)

Report (12)

  • Academic (12)

    • Schoonees, P., Groenen, P., & van de Velden, M. (2015). Least-squares Bilinear Clustering of Three-way Data. (EI report series 2014-23 ed.) Econometric Institute. EI report series Vol. 2014-23

    • van de Velden, M., D'Enza, AI., & Palumbo, F. (2014). Cluster Correspondence Analysis. (EI report serie EI 2014-24 ed.) Econometric Institute. EI report serie Vol. EI 2014-24

    • van de Velden, M., & Takane, Y. (2009). Generalized canonical correlation analysis with missing values. (EI report serie EI 2009-28 ed.) DEPARTMENT OF ECONOMETRICS. EI report serie Vol. EI 2009-28

    • Lorenzo-Seva, U., van de Velden, M., & Kiers, HAL. (2007). Oblique rotation in correspondence analysis: a step forward in the search of the simplest interpretation. (Econometric Institute Report EI 2007-25 ed.) Econometrics. Econometric Institute Report Vol. EI 2007-25

    • Knapp, S., & van de Velden, M. (2007). Visualization of differences across port state control regimes by means of correspondence analysis. (Econometric Institute Report EI 2007-32 ed.) Econometrics. Econometric Institute Report Vol. EI 2007-32

    • van de Velden, M., Groenen, P., & Poblome, J. (2007). Seriation by constrained correspondence analysis: a simulation study. (Econometric Institute Report EI 2007-40 ed.) Econometrics. Econometric Institute Report Vol. EI 2007-40

    • van de Velden, M. (2007). Detecting response styles by using dual scaling of successive categories. (Econometric Institute Report EI 2007-41 ed.) Econometrics. Econometric Institute Report Vol. EI 2007-41

    • Gower, JC., Groenen, P., & van de Velden, M. (2007). Area Biplots. (EI report serie EI 2007-48 ed.) Econometrics. EI report serie Vol. EI 2007-48

    • Torres, A., & van de Velden, M. (2005). Perceptual mapping of multiple variable batteries by plotting supplementary variables in correspondence analysis of rating data. (Econometric Institute Report Serie EI2005-14 ed.) Econometrics. Econometric Institute Report Serie Vol. EI2005-14

    • van de Velden, M., Groenen, P., & Poblome, J. (2005). Seriation mit bedingter Korrespondenzanalyse: Simulationsexperimente. (Econometric Institute Reprint Serie EI-1344 ed.) Econometrics. Econometric Institute Reprint Serie Vol. EI-1344

    • Groenen, P., & van de Velden, M. (2004). Multidimensional scaling. (Econometric Institute EI 2004-15 ed.) Econometric Institute Vol. EI 2004-15

    • Groenen, P., & van de Velden, M. (2002). Inverse correspondence analysis. (Econometric Institute EI 2002-31 ed.) Econometric Institute Vol. EI 2002-31

Working paper (7)

  • Academic (7)

    • Knapp, S., & van de Velden, M. (2024). Predicting inspection outcomes and evaluating port state control targeting using random forests. Econometric Institute, EUR. https://doi.org/10.13140/RG.2.2.26683.43040

    • Knapp, S., & van de Velden, M. (2024). Improved risk predictions of vessels using machine learning: how effective is the status quo? Econometric Institute, EUR. Econometric Institute Research Report Vol. 2024

    • Knapp, S., & van de Velden, M. (2022). Predicting detention and deficiencies using random forests. Econometric Institute, EUR.

    • van de Velden, M., de Beuckelaer, A., Groenen, P., & Busing, FMTA. (2011). Nonmetric unfolding of marketing data: degeneracy and stability. ERIM. ERIM Report Series Vol. 2011-03-11

    • van de Velden, M., Lam, KY., & Franses, P. H. (2011). Visualizing attitudes towards service levels. ERIM. ERIM report series Research in management http://hdl.handle.net/1765/26471

    • Gower, JC., Groenen, P., van de Velden, M., & Vines, K. (2010). Perceptual maps: The good, the bad and the ugly. ERIM. Report Serie Research in Management Vol. ERS-2010-011-MKT

    • Knapp, S., & van de Velden, M. (2010). Visualization of ship risk profiles for the shipping industry. ERIM. ERIM Research in management Vol. 2010-03-23

Additional activities (2)

  • Computational Statistics (Journal)

    Editorial work (Academic)

  • Statistical Papers (Journal)

    Editorial work (Academic)

PhD Tracks (4)

Methods for Modelling Response Styles
  • Role: Member Supervisory Team
  • PhD Candidate: Pieter Schoonees
  • Time frame: 2011 - 2015
  • Role: Daily Supervisor
Inverse methods for data retrieval and simulation
  • Role: Co-promotor
  • PhD Candidate: Rick Willemsen
  • Time frame: 2020 -
Data science for the public sector
  • Role: Daily Supervisor
  • PhD Candidate: Daniël Johannes Wilhelmus Touw
  • Time frame: 2020 -

Events (2)

2013
October
10
On Joint Dimension Reduction and Clustering of Categorical Data
Research Seminar
As: Speaker
2006
November
29
Presenting and discussing grant proposals
ERIM Grant Workshop
As: Speaker

Address

Visiting address

Office: ET-29
Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam
Netherlands

Latest publication

Article

Willemsen, R. S. H., van de Velden, M., & van den Heuvel, W. (2024). On the uniqueness of correspondence analysis solutions. Linear Algebra and Its Applications, 690, 162-185. https://doi.org/10.1016/j.laa.2024.03.014