Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12386/24499| Title: | LIRA: LInear Regression in Astronomy | Authors: | Sereno, Mauro | Issue Date: | 2016 | Journal: | Astrophysics Source Code Library | Abstract: | LIRA (LInear Regression in Astronomy) performs Bayesian linear regression that accounts for heteroscedastic errors in both the independent and the dependent variables, intrinsic scatters (in both variables), time evolution of slopes, normalization and scatters, Malmquist and Eddington bias, and break of linearity. The posterior distribution of the regression parameters is sampled with a Gibbs method exploiting the JAGS (ascl:1209.002) library. | URI: | http://hdl.handle.net/20.500.12386/24499 | URL: | https://ascl.net/1602.006 | Bibcode ADS: | 2016ascl.soft02006S | Fulltext: | open |
| Appears in Collections: | 4.04 Software |
Show full item record
Page view(s)
210
checked on Feb 15, 2025
Download(s)
66
checked on Feb 15, 2025
Google ScholarTM
Check
Items in DSpace are published in Open Access, unless otherwise indicated.