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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.
Package details 


Author  Mauro Sereno 
Maintainer  Mauro Sereno <[email protected]> 
License  GPL2 
Version  2.0.1 
Package repository  View on CRAN 
Installation 
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