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mixl: An open-source R package for estimating complex choice models on large datasets

Author

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  • Molloy, Joseph
  • Becker, Felix
  • Schmid, Basil
  • Axhausen, Kay W.

Abstract

This paper introduces mixl, a new R package for the estimation of advanced choice models. The estimation of such models typically relies on simulation methods with a large number of random draws to obtain stable results. mixl uses inherent properties of the log-likelihood problem structure to greatly reduce both the memory usage and runtime of the estimation procedure for specific types of mixed multinomial logit models. Functions for prediction and posterior analysis are included. Parallel computing is also supported, with near linear speedups observed on up to 24 cores. mixl is directly accessible from R, available on CRAN. We show that mixl is fast, easy to use, and scales to very large datasets. This paper presents the architecture and performance of the package, details its use, and presents some results using real world data and models.

Suggested Citation

  • Molloy, Joseph & Becker, Felix & Schmid, Basil & Axhausen, Kay W., 2021. "mixl: An open-source R package for estimating complex choice models on large datasets," Journal of choice modelling, Elsevier, vol. 39(C).
    • Handle: RePEc:eee:eejocm:v:39:y:2021:i:c:s1755534521000178
    DOI: 10.1016/j.jocm.2021.100284
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    References listed on IDEAS

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    1. Basil Schmid & Milos Balac & Kay W. Axhausen, 2019. "Post-Car World: data collection methods and response behavior in a multi-stage travel survey," Transportation, Springer, vol. 46(2), pages 425-492, April.
    2. Schmid, Basil & Jokubauskaite, Simona & Aschauer, Florian & Peer, Stefanie & Hössinger, Reinhard & Gerike, Regine & Jara-Diaz, Sergio R. & Axhausen, Kay W., 2019. "A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 262-294.
    3. McFadden, Daniel, 1980. "Econometric Models for Probabilistic Choice among Products," The Journal of Business, University of Chicago Press, vol. 53(3), pages 13-29, July.
    4. Czajkowski, Mikołaj & Budziński, Wiktor, 2019. "Simulation error in maximum likelihood estimation of discrete choice models," Journal of choice modelling, Elsevier, vol. 31(C), pages 73-85.
    5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    7. Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
    8. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    9. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    10. Zeileis, Achim, 2006. "Object-oriented Computation of Sandwich Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i09).
    11. van Cranenburgh, Sander & Bliemer, Michiel C.J., 2019. "Information theoretic-based sampling of observations," Journal of choice modelling, Elsevier, vol. 31(C), pages 181-197.
    12. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    13. Schmid, Basil & Axhausen, Kay W., 2019. "In-store or online shopping of search and experience goods: A hybrid choice approach," Journal of choice modelling, Elsevier, vol. 31(C), pages 156-180.
    14. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    15. Arne Henningsen & Ott Toomet, 2011. "maxLik: A package for maximum likelihood estimation in R," Computational Statistics, Springer, vol. 26(3), pages 443-458, September.
    16. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth, 2019. "Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 10(1-2), pages 1-144, January.
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    1. Meister, Adrian & Felder, Matteo & Schmid, Basil & Axhausen, Kay W., 2023. "Route choice modeling for cyclists on urban networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    2. Schmid, Basil & Molloy, Joseph & Peer, Stefanie & Jokubauskaite, Simona & Aschauer, Florian & Hössinger, Reinhard & Gerike, Regine & Jara-Diaz, Sergio R. & Axhausen, Kay W., 2021. "The value of travel time savings and the value of leisure in Zurich: Estimation, decomposition and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 186-215.
    3. Milos Balac & Sebastian Hörl & Basil Schmid, 2024. "Discrete choice modeling with anonymized data," Transportation, Springer, vol. 51(2), pages 351-370, April.
    4. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
    5. Dias, Charitha & Abdullah, Muhammad & Lovreglio, Ruggiero & Sachchithanantham, Sumana & Rekatheeban, Markkandu & Sathyaprasad, I.M.S., 2022. "Exploring home-to-school trip mode choices in Kandy, Sri Lanka," Journal of Transport Geography, Elsevier, vol. 99(C).

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