LInear Regression in Astronomy

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.


Reference manual

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2.0.1 by Mauro Sereno, 3 years ago

Browse source code at

Authors: Mauro Sereno

Documentation:   PDF Manual  

Task views: Chemometrics and Computational Physics

GPL-2 license

Depends on coda, rjags

System requirements: JAGS (>= 3.0.0) (see

See at CRAN