BCES: Linear regression for data with measurement errors and intrinsic scatter

Discussion topics for individual codes
Post Reply
Ada Coda
ASCL Robot
Posts: 2161
Joined: Thu May 08, 2014 5:37 am

BCES: Linear regression for data with measurement errors and intrinsic scatter

Post by Ada Coda » Mon Nov 01, 2021 2:44 am

BCES: Linear regression for data with measurement errors and intrinsic scatter

Abstract: BCES performs robust linear regression on (X,Y) data points where both X and Y have measurement errors. The fitting method is the bivariate correlated errors and intrinsic scatter (BCES). Some of the advantages of BCES regression compared to ordinary least squares fitting are that it allows for measurement errors on both variables and permits the measurement errors for the two variables to be dependent. Further it permits the magnitudes of the measurement errors to depend on the measurements and other lines such as the bisector and the orthogonal regression can be constructed.

Credit: Nemmen, Rodrigo

Site: https://github.com/rsnemmen/BCES
https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.2067C

Bibcode: 2021ascl.soft10020N

Preferred citation method: https://ui.adsabs.harvard.edu/abs/1996ApJ...470..706A and https://ui.adsabs.harvard.edu/abs/2012Sci...338.1445N

ID: ascl:2110.020

Post Reply