icmstate-package: icmstate
In icmstate: Interval Censored Multi-State Models
icmstate-package R Documentation
icmstate
Description
Non-parametric estimation of transition intensities in
interval-censored multi-state models
Details
Allows for the estimation of transition intensities in interval-censored
multi-state models using the approach of Gomon and Putter (2024) (Multinomial likelihood) or
Gu et al. (2023) (Poisson likelihood).
Author(s)
Maintainer: Daniel Gomon <dgstatsoft@gmail.com> [aut, cre]
Hein Putter [aut]
References
Y. Gu, D. Zeng, G. Heiss, and D. Y. Lin,
Maximum likelihood estimation for semiparametric regression models with
interval-censored multistate data, Biometrika, Nov. 2023, doi:10.1093/biomet/asad073
D. Gomon and H. Putter,
Non-parametric estimation of transition intensities in interval censored Markov multi-state models without loops,
arXiv, 2024, doi:10.48550/arXiv.2409.07176
icmstate documentation built on April 3, 2025, 8:06 p.m.
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| icmstate-package | R Documentation |
icmstate
Description
Non-parametric estimation of transition intensities in interval-censored multi-state models
Details
Allows for the estimation of transition intensities in interval-censored multi-state models using the approach of Gomon and Putter (2024) (Multinomial likelihood) or Gu et al. (2023) (Poisson likelihood).
Author(s)
Maintainer: Daniel Gomon <dgstatsoft@gmail.com> [aut, cre]
Hein Putter [aut]
References
Y. Gu, D. Zeng, G. Heiss, and D. Y. Lin, Maximum likelihood estimation for semiparametric regression models with interval-censored multistate data, Biometrika, Nov. 2023, doi:10.1093/biomet/asad073
D. Gomon and H. Putter, Non-parametric estimation of transition intensities in interval censored Markov multi-state models without loops, arXiv, 2024, doi:10.48550/arXiv.2409.07176
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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