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Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application
Abstract
Abstract The community of choice modellers has expanded substantially over recent years, covering many disciplines and encompassing users with very different levels of econometric and computational skills. This paper presents an introduction to Apollo, a powerful new freeware package for R that aims to provide a comprehensive set of modelling tools for both new and experienced users. Apollo also incorporates numerous post-estimation tools, allows for both classical and Bayesian estimation, and permits advanced users to develop their own routines for new model structures.
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Citations
Cited by
Szinay, D., Cameron, R., Naughton, F., Whitty, J. A., Brown, J., & Jones, A. (2021) · Journal of Medical Internet Research · doi:10.2196/32365 · Cited by 106
Buckell, J., Wreford, A., Quaife, M., & Hancock, T. O. (2025) · Medical Decision Making · doi:10.1177/0272989x251357879 · Cited by 3
Metadata
- Authors
- Hess, S., & Palma, D.
- Venue
- Journal of Choice Modelling
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 32
- Pages
- 100170
- ISSN
- 1755-5345 (ISSN-L)
- OpenAlex
- W2948220358
- Cited by
- 953
- References
- 0
- FWCI
- 76.99
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hess, S., & Palma, D. (2019). Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application. Journal of Choice Modelling. https://doi.org/10.1016/j.jocm.2019.100170
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
