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MSmix: Finite Mixtures of Mallows Models with Spearman Distance for Full and Partial Rankings
Fit and analysis of finite Mixtures of Mallows models with Spearman Distance for full and partial rankings with arbitrary missing positions. Inference is conducted within the maximum likelihood framework via Expectation-Maximization algorithms. Estimation uncertainty is tackled via diverse versions of bootstrapped and asymptotic confidence intervals. The most relevant reference of the methods is Crispino, Mollica, Astuti and Tardella (2023) <doi:10.1007/s11222-023-10266-8>.
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Package details |
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| Author | Cristina Mollica [aut, cre, cph] (<https://orcid.org/0000-0001-9152-6021>), Marta Crispino [aut, cph] (<https://orcid.org/0000-0002-1818-1298>), Lucia Modugno [ctb] (<https://orcid.org/0009-0003-7212-3237>), Luca Tardella [ctb] (<https://orcid.org/0000-0002-5703-3909>) |
| Maintainer | Cristina Mollica <cristina.mollica@uniroma1.it> |
| License | GPL (>= 3) |
| Version | 2.0.0 |
| Package repository | View on CRAN |
| Installation |
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