Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python
By Matthew Newville, Antonino Ingargiola, T. Stensitzki, Daniel B. Allen. 2014
1,627 citations recorded by the source corpus.
Subfields: Applied Mathematics, Artificial Intelligence, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/d0bbb66514d75543d8922ed02c50990808e68991
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In Applied Mathematics
In Artificial Intelligence
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Citations in the corpus
- RadVel: The Radial Velocity Modeling Toolkit (2018, methodology): “We modeled this dictionary representation after the lmfit (Newville et al. 2014) API which allows users to conveniently interface with variables via string keys (as opposed to integer indexes).”
- The California-Kepler Survey. VII. Precise Planet Radii Leveraging Gaia DR2 Reveal the Stellar Mass Dependence of the Planet Radius Gap (2018, methodology): “We made use of the following publicly available Python modules: astropy (Astropy Collaboration et al. 2013), isoclassify (Huber et al. 2017), lmfit (Newville et al. 2014), matplotlib (Hunter 2007), numpy/scipy (van der Walt et al. 2011), and pandas (McKinney 2010).”
- The California-Kepler Survey. III. A Gap in the Radius Distribution of Small Planets (2017, methodology): “Using the lmfit Python package (Newville et al. 2014) to minimize the residuals we found best-fit values of k = 17.56, l = 1.00 (fixed), and θ = 0.49.”
- Precision Stellar Characterization of FGKM Stars using an Empirical Spectral Library (2017, methodology): “Allowing for v sin i and continuum normalization to float as free parameters, we use a non-linear leastsquares minimization package lmfit (Newville et al. 2014) to minimize χ2, finding the best possible match between the target and reference spectra.”
- The California-Kepler Survey. IV. Metal-rich Stars Host a Greater Diversity of Planets (2017, methodology): “We made use of the following publicly available python modules: astropy (Astropy Collaboration et al. 2013), isoclassify Huber et al. (2017), lmfit (Newville et al. 2014), matplotlib (Hunter 2007), numpy, pandas http://pandas.pydata.org/, and scipy (Jones et al. 2001–) REFERENCES Adams, E. R.,…”
- Population flow drives spatio-temporal distribution of COVID-19 in China (2020, methodology): “Data analysis We used the Levenberg–Marquardt (LM) algorithm for model estimation, and the code was from Newville et al. (2016); Software includes Matlab (R2018a, The MathWorks, Inc.), Python (V.3.7.4, Python Software Foundation), and ArcGIS (V.10.2, Esri).”