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r-cran-pammtools package

r-cran-pammtools 0.5.92-1 source package in Ubuntu

Changelog

r-cran-pammtools (0.5.92-1) unstable; urgency=medium

  * New upstream version
  * dh-update-R to update Build-Depends (routine-update)
  * Remove trailing whitespace in debian/changelog (routine-update)
  * Set upstream metadata fields: Repository-Browse.

 -- Andreas Tille <email address hidden>  Fri, 01 Sep 2023 11:43:52 +0200

Upload details

Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular release universe misc
Noble release universe misc

Builds

Noble: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-pammtools_0.5.92-1.dsc 2.3 KiB 895b0b0c787060c7c9f226ec998f7319efbc4fe86d1ed72b0fbebca10bd0826e
r-cran-pammtools_0.5.92.orig.tar.gz 377.7 KiB ccf9d930521af76d441d82bf08b89e125f237f81df1f50a8152c13c9bf73e401
r-cran-pammtools_0.5.92-1.debian.tar.xz 3.4 KiB 4a290fc70dd0ec26c00c29b9cddc1d3173203fbc25bd5016556a0652cf37e4a6

Available diffs

No changes file available.

Binary packages built by this source

r-cran-pammtools: GNU R piece-wise exponential additive mixed modeling tools

 This package provides piece-wise exponential additive mixed modeling
 tools for survival analysis. The Piece-wise exponential (Additive Mixed)
 Model (PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>)
 is a powerful model class for the analysis of survival (or time-to-
 event) data, based on Generalized Additive (Mixed) Models (GA(M)Ms). It
 offers intuitive specification and robust estimation of complex survival
 models with stratified baseline hazards, random effects, time-varying
 effects, time-dependent covariates and cumulative effects (Bender and
 others (2019)), as well as support for left-truncated, competing risks
 and recurrent events data. pammtools provides tidy workflow for survival
 analysis with PAMMs, including data simulation, transformation and other
 functions for data preprocessing and model post-processing as well as
 visualization.