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Hyper-Fit: Fitting routines for multidimensional data with multivariate Gaussian uncertainties

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Ada Coda
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Hyper-Fit: Fitting routines for multidimensional data with multivariate Gaussian uncertainties

Postby Ada Coda » Thu Jan 14, 2016 9:21 am

Hyper-Fit: Fitting routines for multidimensional data with multivariate Gaussian uncertainties

Abstract: The R package Hyper-Fit fits hyperplanes (hyper.fit) and creates 2D/3D visualizations (hyper.plot2d / hyper.plot3d) to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimensional dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane. A web interface for online fitting is also available at http://hyperfit.icrar.org.

Credit: Robotham, Aaron S.G.; Obreschkow, Danail

Site: https://github.com/asgr/hyper.fit
http://adsabs.harvard.edu/abs/2015PASA...32...33R

Bibcode: 2016ascl.soft01002R

ID: ascl:1601.002
Last edited by Ada Coda on Thu Jan 14, 2016 9:23 am, edited 1 time in total.
Reason: Updated code entry.

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