SLOPES: Least-squares linear regression lines for bivariate

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SLOPES: Least-squares linear regression lines for bivariate datasets

Post by owlice » Tue Jul 27, 2010 12:39 pm

[c]SLOPES: Least-squares linear regression lines for bivariate datasets[/c][/b]
Abstract: SLOPES computes six least-squares linear regression lines for bivariate datasets of the form (x_i,y_i) with unknown population distributions. Measurement errors, censoring (nondetections) or other complications are not treated. The lines are: the ordinary least-squares regression of y on x, OLS(Y|X); the inverse regression of x on y, OLS(X_Y); the angular bisector of the OLS lines; the orthogonal regression line; the reduced major axis, and the mean-OLS line. The latter four regressions treat the variables symmetrically, while the first two regressions are asymmetrical. Uncertainties for the regression coefficients of each method are estimated via asymptotic formulae, bootstrap resampling, and bivariate normal simulation. These methods, derivation of the regression coefficient uncertainties, and discussions of their use are provided in three papers listed below. The user is encouraged to read and reference these studies.

Credit: Feigelson, Eric

Site: https://web.archive.org/web/20130122223 ... s/slopes.f
https://ui.adsabs.harvard.edu/#abs/1990ApJ...364..104I/

Bibcode: 1999ascl.soft06001F

ID: ascl:9906.001
Last edited by Ada Coda on Tue Jun 19, 2018 5:36 pm, edited 1 time in total.
Reason: Updated code entry.
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