The mlt package implements maximum likelihood estimation in conditional transformation models as introduced by Hothorn et al. (2020), Klein et al. (2022), and Siegfried et al. (2023).
An introduction to the package is available in the mlt package
vignette from package mlt.docreg (Hothorn, 2020).
Novice users might find the high(er) level interfaces offered by package tram more convenient.
This package is authored by Torsten Hothorn <Torsten.Hothorn@R-project.org>.
Torsten Hothorn, Lisa Moest, Peter Buehlmann (2018), Most Likely Transformations, Scandinavian Journal of Statistics, 45(1), 110--134, tools:::Rd_expr_doi("10.1111/sjos.12291").
Torsten Hothorn (2020), Most Likely Transformations: The mlt Package, Journal of Statistical Software, 92(1), 1--68, tools:::Rd_expr_doi("10.18637/jss.v092.i01")
Nadja Klein, Torsten Hothorn, Luisa Barbanti, Thomas Kneib (2022), Multivariate Conditional Transformation Models. Scandinavian Journal of Statistics, 49, 116--142, tools:::Rd_expr_doi("10.1111/sjos.12501").
Sandra Siegfried, Lucas Kook, Torsten Hothorn (2023), Distribution-Free Location-Scale Regression, The American Statistician, 77(4), 345--356, tools:::Rd_expr_doi("10.1080/00031305.2023.2203177").
Torsten Hothorn (2024), On Nonparanormal Likelihoods. tools:::Rd_expr_doi("10.48550/arXiv.2408.17346").