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Performs Bayesian linear regression and forecasting in astronomy. The method accounts for heteroscedastic errors in both the independent and the dependent variables, intrinsic scatters (in both variables) and scatter correlation, time evolution of slopes, normalization, scatters, Malmquist and Eddington bias, upper limits and break of linearity. The posterior distribution of the regression parameters is sampled with a Gibbs method exploiting the JAGS library.
| Version: | 2.0.1 |
| Depends: | R (≥ 2.14.0), coda, rjags |
| Published: | 2018-02-06 |
| DOI: | 10.32614/CRAN.package.lira |
| Author: | Mauro Sereno |
| Maintainer: | Mauro Sereno <mauro.sereno at unibo.it> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| SystemRequirements: | JAGS (>= 3.0.0) (see http://mcmc-jags.sourceforge.net) |
| In views: | ChemPhys |
| CRAN checks: | lira results |
| Reference manual: | lira.pdf |
| Package source: | lira_2.0.1.tar.gz |
| Windows binaries: | r-devel: lira_2.0.1.zip, r-release: lira_2.0.1.zip, r-oldrel: lira_2.0.1.zip |
| macOS binaries: | r-release (arm64): lira_2.0.1.tgz, r-oldrel (arm64): lira_2.0.1.tgz, r-release (x86_64): lira_2.0.1.tgz, r-oldrel (x86_64): lira_2.0.1.tgz |
| Old sources: | lira archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.