r-cran-statmod 1.4.21-1 source package in Ubuntu
Changelog
r-cran-statmod (1.4.21-1) unstable; urgency=medium * Imported Upstream version 1.4.21 * d/control: overhaul short and long descriptions. * Bump Standards-Version to 3.9.6, no changes needed. * d/copyright: update copyright dates. -- Sébastien Villemot <email address hidden> Thu, 30 Apr 2015 15:18:26 +0200
Upload details
- Uploaded by:
- Debian Science Team
- Uploaded to:
- Sid
- Original maintainer:
- Debian Science Team
- Architectures:
- any
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| r-cran-statmod_1.4.21-1.dsc | 2.0 KiB | 79d80cae5c69aa04e98960bfd30b122b8b515e0997f0132a81ad841fd254a111 |
| r-cran-statmod_1.4.21.orig.tar.gz | 54.9 KiB | aa996fe93f0bd5635d40783039eb868811a9238e83e0a5a7da8617a17082148d |
| r-cran-statmod_1.4.21-1.debian.tar.xz | 2.1 KiB | 0077ff7167a00732ed19610ab9dccafbc2c8afd04a5bbc2d1b2ccafc211ad127 |
Available diffs
- diff from 1.4.20-1 to 1.4.21-1 (8.4 KiB)
No changes file available.
Binary packages built by this source
- r-cran-statmod: GNU R package providing algorithms and functions for statistical modeling
This R package provides a collection of algorithms and functions to aid
statistical modeling. It includes growth curve comparisons, limiting dilution
analysis (aka ELDA), mixed linear models, heteroscedastic regression,
inverse-Gaussian probability calculations, Gauss quadrature and a secure
convergence algorithm for nonlinear models. It also includes advanced
generalized linear model functions that implement secure convergence,
dispersion modeling and Tweedie power-law families.
- r-cran-statmod-dbgsym: debug symbols for package r-cran-statmod
This R package provides a collection of algorithms and functions to aid
statistical modeling. It includes growth curve comparisons, limiting dilution
analysis (aka ELDA), mixed linear models, heteroscedastic regression,
inverse-Gaussian probability calculations, Gauss quadrature and a secure
convergence algorithm for nonlinear models. It also includes advanced
generalized linear model functions that implement secure convergence,
dispersion modeling and Tweedie power-law families.
