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    "info": {
        "author": "Michele Cappellari",
        "author_email": "michele.cappellari@physics.ox.ac.uk",
        "bugtrack_url": null,
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            "Development Status :: 5 - Production/Stable",
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            "Intended Audience :: Science/Research",
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        "description": "The LtsFit Package\n==================\n\n**Robust Linear Regression with Scatter in One or Two Dimensions**\n\n.. image:: https://img.shields.io/pypi/v/ltsfit.svg\n        :target: https://pypi.org/project/ltsfit/\n.. image:: http://img.shields.io/badge/arXiv-1208.3522-orange.svg\n    :target: https://arxiv.org/abs/1208.3522\n.. image:: https://img.shields.io/badge/DOI-10.1093/mnras/stt562-blue.svg\n        :target: https://doi.org/10.1093/mnras/stt562\n\nLtsFit is a Python implementation of the method described in Section 3.2 of\n`Cappellari et al. (2013a) <http://adsabs.harvard.edu/abs/2013MNRAS.432.1709C>`_\nto perform **very robust** fits of lines or planes to data with errors in all\ncoordinates, while allowing for possible intrinsic scatter.\nOutliers are iteratively clipped using the robust Least Trimmed Squares (LTS)\ntechnique by `Rousseeuw & van Driessen (2006)\n<http://dx.doi.org/10.1007/s10618-005-0024-4>`_.\n\nAttribution\n-----------\n\nIf you use this software for your research, please cite\n`Cappellari et al. (2013a) <http://adsabs.harvard.edu/abs/2013MNRAS.432.1709C>`_\nwhere the implementation was described. The BibTeX entry for the paper is::\n\n    @ARTICLE{Cappellari2013a,\n        author = {{Cappellari}, M. and {Scott}, N. and {Alatalo}, K. and\n            {Blitz}, L. and {Bois}, M. and {Bournaud}, F. and {Bureau}, M. and\n            {Crocker}, A.~F. and {Davies}, R.~L. and {Davis}, T.~A. and {de Zeeuw},\n            P.~T. and {Duc}, P.-A. and {Emsellem}, E. and {Khochfar}, S. and\n            {Krajnovi{\\'c}}, D. and {Kuntschner}, H. and {McDermid}, R.~M. and\n            {Morganti}, R. and {Naab}, T. and {Oosterloo}, T. and {Sarzi}, M. and\n            {Serra}, P. and {Weijmans}, A.-M. and {Young}, L.~M.},\n        title = \"{The ATLAS$^{3D}$ project - XV. Benchmark for early-type\n            galaxies scaling relations from 260 dynamical models: mass-to-light\n            ratio, dark matter, Fundamental Plane and Mass Plane}\",\n        journal = {MNRAS},\n        eprint = {1208.3522},\n        year = 2013,\n        volume = 432,\n        pages = {1709-1741},\n        doi = {10.1093/mnras/stt562}\n    }\n\nInstallation\n------------\n\ninstall with::\n\n    pip install ltsfit\n\nWithout writing access to the global ``site-packages`` directory, use::\n\n    pip install --user ltsfit\n\nDocumentation\n-------------\n\nSee ``ltsfit/examples`` and the files headers.\n\nLicense\n-------\n\nCopyright (c) 2012-2018 Michele Cappellari\n\nThis software is provided as is without any warranty whatsoever.\nPermission to use, for non-commercial purposes is granted.\nPermission to modify for personal or internal use is granted,\nprovided this copyright and disclaimer are included in all\ncopies of the software. All other rights are reserved.\nIn particular, redistribution of the code is not allowed.",
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