Package: SmoothHazard
Title: Estimation of Smooth Hazard Models for Interval-Censored Data
with Applications to Survival and Illness-Death Models
Version: 2022.08.23
Author: Celia Touraine, Pierre Joly, Thomas A. Gerds
Description: Estimation of two-state (survival) models and irreversible illness-
death models with possibly interval-censored,left-truncated and right-censored
data. Proportional intensities regression models can be specified to allow for
covariates effects separately for each transition. We use either a parametric
approach with Weibull baseline intensities or a semi-parametric approach with
M-splines approximation of baseline intensities in order to obtain smooth
estimates of the hazard functions. Parameter estimates are obtained by maximum
likelihood in the parametric approach and by penalized maximum likelihood in the
semi-parametric approach.
Encoding: UTF-8
Depends: R (>= 1.9.1), prodlim (>= 1.4.9)
Imports: lava (>= 1.4.1), mvtnorm (>= 1.0-3)
Maintainer: Thomas Alexander Gerds <tag@biostat.ku.dk>
License: GPL (>= 2)
Packaged: 2022-08-24 06:16:44 UTC; tag
RoxygenNote: 7.2.0
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2022-08-24 07:00:19 UTC

Title: A Collection of Smooth Tensor Estimation Methods
Authors@R: c(person("Chanwoo","Lee", role = c("aut", "cre"),
person("Miaoyan", "Wang", role = "aut", email = "miaoyan.wang@wisc.edu") )
Description: A list of methods for estimating a smooth tensor with an unknown permutation. It also contains several multi-variate functions for generating permuted signal tensors and corresponding observed tensors. For a detailed introduction for the model and estimation techniques, see the paper by Chanwoo Lee and Miaoyan Wang (2021) "Smooth tensor estimation with unknown permutations" <arXiv:2105.01783>.
Packaged: 2021-11-10 00:29:51 UTC; chanwoolee

Description: A list of methods for estimating a smooth tensor with an unknown permutation. It also contains several multi-variate functions for generating permuted signal tensors and corresponding observed tensors. For a detailed introduction for the model and estimation techniques, see the paper by Chanwoo Lee and Miaoyan Wang (2021) "Smooth tensor estimation with unknown permutations" <arXiv:2111.04681>.
Packaged: 2021-11-14 21:19:12 UTC; chanwoolee