dr.

(Michel) M van de Velden

Profile

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.

• All publications (56)

  • Article (35)

    • Scholarly Publication (33)

      • M. van de Velden, W. van den Heuvel, P.J.F. Groenen & H. Galy (2020). Retrieving a contingency table from a correspondence analysis solution. European Journal of Operational Research, 283 (2), 541-548. doi: 10.1016/j.ejor.2019.11.014
      • M. van de Velden, A. Iodice D'Enza & M. Yamamoto (2019). Special feature: dimension reduction and cluster analysis. Behaviormetrika, 46 (2), 239-241. doi: 10.1007/s41237-019-00092-6
      • L. Bransen, J. van Haaren & M. van de Velden (2019). Measuring soccer players’ contributions to chance creation by valuing their passes. Journal of Quantitative Analysis in Sports, 15 (2). doi: 10.1515/jqas-2018-0020 [go to publisher's site]
      • A. Torres, J. César Machado, L. Vacas de Carvalho, M. van de Velden & P. Costa (2019). Same design, same response? Investigating natural designs in international logos. The Journal of Product and Brand Management, 28 (3), 317-329. doi: 10.1108/JPBM-10-2017-1632
      • U. Lorenzo-Seva & M. van de Velden (2019). MultipleCar: A Graphical User Interface MATLAB Toolbox to Compute Multiple Correspondence Analysis. Journal of Statistical Software, 90 (4). doi: 10.18637/jss.v090.i04
      • A. Markos, A. Iodice D'Enza & M. van de Velden (2019). Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R. Journal of Statistical Software, 91 (10). doi: 10.18637/jss.v091.i10
      • M. Takagishi, M. van de Velden & H. Yadohisa (2019). Clustering preference data in the presence of response‐style bias. British Journal of Mathematical and Statistical Psychology, 72, 401-425. doi: 10.1111/bmsp.12170
      • M. van de Velden, A. Iodice D'Enza & A. Markos (2018). Distance-based clustering of mixed data. Wiley Interdisciplinary Reviews. Computational Statistics. doi: 10.1002/wics.1456
      • M. van de Velden, A. Iodice D'Enza & F. Palumbo (2017). cluster correspondence analysis. Psychometrika, 82 (1), 158-185. doi: 10.1007/s11336-016-9514-0 [go to publisher's site]
      • P.J.F. Groenen & M. van de Velden (2016). Multidimensional Scaling by Majorization: A Review. Journal of Statistical Software, 73 (8), 1-26. doi: 10.18637/jss.v073.i08
      • J. van Dam & M. van de Velden (2015). Online profiling and clustering of Facebook users. Decision Support Systems, 70, 60-72. doi: 10.1016/j.dss.2014.12.001
      • P.C. Schoonees, M. van de Velden & P.J.F. Groenen (2015). Constrained Dual Scaling for Detecting Response Styles in Categorical Data. Psychometrika, 80 (4), 968-994. doi: 10.1007/s11336-015-9458-9
      • J.C. Gower, P.J.F. Groenen, M. van de Velden & K. Vines (2014). Better perceptual maps: Introducing explanatory icons to facilitate interpretation. Food Quality and Preference, 36, 61-69. doi: 10.1016/j.foodqual.2014.01.004
      • M. van de Velden, A. de Beuckelaer, P.J.F. Groenen & F.M.T.A. Busing (2013). Solving degeneracy and stability in nonmetric unfolding. Food Quality and Preference, 27 (1), 85-95. doi: 10.1016/j.foodqual.2012.06.010
      • I. Kim, M. Kim, M. van de Velden & H. Lee (2013). Psychological positioning of bottled tea products: A comparison between two Kansei profiling techniques. Food Science and Biotechnology, 22 (1), 257-268. doi: 10.1007/s10068-013-0035-7
      • M. van de Velden & Y. Takane (2012). Generalized canonical correlation analysis with missing values. Computational Statistics, 27 (3), 551-571. doi: 10.1007/s00180-011-0276-y
      • T.H.A. Bijmolt & M. van de Velden (2012). Multi-attribute perceptual mapping using idiosyncratic brand and attribute sets. Marketing Letters, 23 (3), 585-601. doi: 10.1007/s11002-012-9163-8
      • S. Knapp & M. van de Velden (2011). Global ship risk profiles: Safety and the marine environment. Transportation Research. Part D, Transport and Environment, 16 (8), 595-560. doi: 10.1016/j.trd.2011.08.001
      • J.C. Gower, P.J.F. Groenen & M. van de Velden (2010). Area biplots. Journal of Computational and Graphical Statistics, 19 (1), 46-61. doi: 10.1198/jcgs.2010.07134
      • M. van de Velden, P.J.F. Groenen & J. Poblome (2009). Seriation by constrained correspondence analysis: A simulation study. Computational Statistics & Data Analysis, 53 (8), 3129-3138. doi: 10.1016/j.csda.2008.08.020
      • J. Blasius, M. Greenarcre, P.J.F. Groenen & M. van de Velden (2009). Special issue on correspondence analysis and related methods. Computational Statistics & Data Analysis, 53 (8), 3103-3106. doi: 10.1016/j.csda.2008.11.010
      • S. Knapp & M. van de Velden (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. doi: 10.1080/01441640802573749
      • U. Lorenzo-Seva, M. van de Velden & H.A.L. Kiers (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. doi: 10.1348/000711008X368295
      • U. Lorenzo-Seva, M. van de Velden & H.A.L. Kiers (2009). CAR: A MATLAB Package to Compute Correspondence Analysis with Rotations. Journal of Statistical Software, 31 (8), 1-14. doi: 10.18637/jss.v031.i08
      • A. Torres & M. van de Velden (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. doi: 10.1016/j.foodqual.2005.09.005
      • H. van Herk & M. van de Velden (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. doi: 10.1016/j.foodqual.2007.05.006
      • M. van de Velden & T.H.A. Bijmolt (2006). Generalized canonical correlation analysis of matrices with missing rows: a simulation study. Psychometrika, 71, 323-331. doi: 10.1007/s11336-004-1168-9
      • M. van de Velden & T.H.A. Bijmolt (2005). A Visualization of the Dutch political landscape using generalized canonical correlation analysis. Medium Econometrische Toepassingen, 13 (2), 20-24.
      • M. van de Velden & H.A.L. Kiers (2005). Rotation in Correspondence Analysis. Journal of Classification, 22, 251-271. doi: 10.1007/s00357-005-0016-5
      • M. van de Velden (2004). Optimal scaling of paired comparison data. Journal of Classification, 21, 89-109.
      • P.J.F. Groenen & M. van de Velden (2004). Inverse correspondence analysis. Linear Algebra and its Applications, 388, 221-238. doi: 10.1016/j.laa.2003.10.016
      • M. van de Velden, P.J.F. Groenen & J. Poblome (2003). Seriation met bedingter Korrespondenzanalyse: Simulationsexperimente. Archaologische informationen, 26, 449-455.
      • M. van de Velden & H. Neudecker (2000). On an eigenvalue property relevant in correspondence analysis and related methods. Linear Algebra and its Applications, 321, 347-364.

    • Professional Publication (2)

      • L.F.M. Groot & M. van de Velden (2010). De WK-poulewijzer. Economisch-Statistische Berichten, 95, 362-364.
      • B. Karsemeijer, P.H.B.F. Franses & M. van de Velden (2007). Saaie Winkelstraten. Economisch-Statistische Berichten, 746.

  • Part of book - Chapter (2)

    • A. Iodice D'Enza, P.J.F. Groenen & M. van de Velden (2020). PowerCA: A Fast Iterative Implementation of Correspondence Analysis. In T Imaizumi, A Nakayama & S Yokoyama (Eds.), Advanced Studies in Behaviormetrics and Data Science (Behaviormetrics: Quantitative Approaches to Human Behavior) (pp. 283-296). Singapore: Springer doi: 10.1007/978-981-15-2700-5
    • M. van de Velden (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 (Advanced studies in theoretical and applied econometrics, 36) (pp. 87-99). Boston, U.S.A.: Kluwer Academic Publisher

  • Report (16)

    • P.C. Schoonees, P.J.F. Groenen & M. van de Velden (2015). Least-squares Bilinear Clustering of Three-way Data. (Intern rapport, EI report series, no 2014-23). Rotterdam: Econometric Institute
    • M. van de Velden, A.I. D'Enza & F. Palumbo (2014). Cluster Correspondence Analysis. (Intern rapport, EI report serie, no EI 2014-24). Rotterdam: Econometric Institute
    • M. van de Velden, K.Y. Lam & P.H.B.F. Franses (2011). Visualizing attitudes towards service levels. (Preprints, ERIM report series Research in management). Rotterdam: ERIM
    • M. van de Velden, A. de Beuckelaer, P.J.F. Groenen & F.M.T.A. Busing (2011). Nonmetric unfolding of marketing data: degeneracy and stability. (Preprints, ERIM Report Series, no 2011-03-11). Rotterdam: ERIM
    • J.C. Gower, P.J.F. Groenen, M. van de Velden & K. Vines (2010). Perceptual maps: The good, the bad and the ugly. (Preprints, Report Serie Research in Management, no ERS-2010-011-MKT). 3000 DR Rotterdam: ERIM
    • S. Knapp & M. van de Velden (2010). Visualization of ship risk profiles for the shipping industry. (Preprints, ERIM Research in management, no 2010-03-23). 3000 DR Rotterdam: ERIM
    • M. van de Velden & Y. Takane (2009). Generalized canonical correlation analysis with missing values. (Intern rapport, EI report serie, no EI 2009-28). 3000 DR Rotterdam: DEPARTMENT OF ECONOMETRICS
    • U. Lorenzo-Seva, M. van de Velden & H.A.L. Kiers (2007). Oblique rotation in correspondence analysis: a step forward in the search of the simplest interpretation. (Intern rapport, Econometric Institute Report, no EI 2007-25). 3000 DR Rotterdam: Econometrics
    • S. Knapp & M. van de Velden (2007). Visualization of differences across port state control regimes by means of correspondence analysis. (Intern rapport, Econometric Institute Report, no EI 2007-32). 3000 DR Rotterdam: Econometrics
    • M. van de Velden, P.J.F. Groenen & J. Poblome (2007). Seriation by constrained correspondence analysis: a simulation study. (Intern rapport, Econometric Institute Report, no EI 2007-40). 3000 DR Rotterdam: Econometrics
    • J.C. Gower, P.J.F. Groenen & M. van de Velden (2007). Area Biplots. (Intern rapport, EI report serie, no EI 2007-48). 3000 DR Rotterdam: Econometrics
    • M. van de Velden (2007). Detecting response styles by using dual scaling of successive categories. (Intern rapport, Econometric Institute Report, no EI 2007-41). 3000 DR Rotterdam: Econometrics
    • M. van de Velden, P.J.F. Groenen & J. Poblome (2005). Seriation mit bedingter Korrespondenzanalyse: Simulationsexperimente. (Intern rapport, Econometric Institute Reprint Serie, no EI-1344). 3000 DR Rotterdam: Econometrics
    • A. Torres & M. van de Velden (2005). Perceptual mapping of multiple variable batteries by plotting supplementary variables in correspondence analysis of rating data. (Intern rapport, Econometric Institute Report Serie, no EI2005-14). 3000 DR Rotterdam: Econometrics
    • P.J.F. Groenen & M. van de Velden (2004). Multidimensional scaling. (Intern rapport, Econometric Institute, no EI 2004-15). :
    • P.J.F. Groenen & M. van de Velden (2002). Inverse correspondence analysis. (Intern rapport, Econometric Institute, no EI 2002-31). :

  • Article in volume (3)

    • M. van de Velden (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). tokyo: universal academy press
    • P.J.F. Groenen & M. van de Velden (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)
    • M. van de Velden & H.A.L. Kiers (2003). 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). Tokyo: Springer Verlag

• Ancillary activities (3)

  EQI

  Start date approval

  Jul/2019

  End date approval

  Jul/2022

  Place

  ROTTERDAM

  Erasmus Academie

  Start date approval

  Jul/2019

  End date approval

  Jul/2022

  Place

  ROTTERDAM

  Ver. voor Statistiek en Operationele Research

  Start date approval

  Jul/2019

  End date approval

  Jul/2022

  Place

  WAGENINGEN

• Teaching (5)

  Seminar Data Science for Marketing Analy

  Title

  Seminar Data Science for Marketing Analy

  Year

  2020

  Year level

  master

  Applied Statistics 1

  Title

  Applied Statistics 1

  Year

  2020

  Year level

  bachelor 1, bachelor 1, bachelor 1

  Applied Statistics 1

  Title

  Applied Statistics 1

  Year

  2020

  Year level

  bachelor 1, bachelor 1, bachelor 1

  Applied Statistics 1

  Title

  Applied Statistics 1

  Year

  2020

  Year level

  bachelor 1

  Applied Statistics 1

  Title

  Applied Statistics 1

  Year

  2020

  Year level

  bachelor 1

• PhD list (3)

  • Rick Willemsen

    Inverse methods for data retrieval and simulation

    • 2020 -

  • Daniël Johannes Wilhelmus Touw

    Data science for the public sector

    • 2020 -
  • Pieter Schoonees

    Methods for Modelling Response Styles

    • 2011 - 2015

• Editorial positions (2)

  Computational Statistics

  Role

  Associate Editor

  Start date approval

  Nov/2011

  Statistical Papers

  Additional Information

  Editor Problem Section

  Role

  Special Section Editor

  Start date approval

  Feb/2008

  End date approval

  Sep/2017

• Present position

  Associate Professor

  University

  Erasmus University Rotterdam

  School

  Erasmus School of Economics

  Department

  Econometrics

  Country

  The Netherlands

  Telephone

  0104088692