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Nonparametric approaches to describing heterogeneity

In: Handbook of Choice Modelling

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  • Mogens Fosgerau

Abstract

This chapter considers the estimation of binomial and multinomial discrete choice models that contain a random preference parameter with an unknown distribution, focusing on simple approaches where this unknown distribution is directly estimated.

Suggested Citation

  • Mogens Fosgerau, 2024. "Nonparametric approaches to describing heterogeneity," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 11, pages 308-318, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:20188_11
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    File URL: https://www.elgaronline.com/doi/10.4337/9781800375635.00018
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    2. Claudia Bazzani & Marco A. Palma & Rodolfo M. Nayga, 2018. "On the use of flexible mixing distributions in WTP space: an induced value choice experiment," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), pages 185-198, April.
    3. Yuan, Yuan & You, Wen & Boyle, Kevin J., 2015. "A guide to heterogeneity features captured by parametric and nonparametric mixing distributions for the mixed logit model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205733, Agricultural and Applied Economics Association.
    4. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.

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