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These packages facilitate least-squares fitting of noisy data by multi-dimensional, nonlinear functions of arbitrarily many parameters. The central package is :mod:`lsqfit` which provides the fitting capability. :mod:`lsqfit` makes heavy use of package :mod:`gvar`, which provides tools for the analysis of error propagation, and also for the creation of complicated multi-dimensional gaussian distributions. :mod:`lsqfit` supports Bayesian priors for the fit parameters, with arbitrarily complicated multidimensional gaussian distributions. It uses automatic differentiation to compute gradients, greatly simplifying the design of fit functions.
11 lines
647 B
Text
11 lines
647 B
Text
These packages facilitate least-squares fitting of noisy data by
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multi-dimensional, nonlinear functions of arbitrarily many
|
|
parameters. The central package is :mod:`lsqfit` which provides
|
|
the fitting capability. :mod:`lsqfit` makes heavy use of package
|
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:mod:`gvar`, which provides tools for the analysis of error
|
|
propagation, and also for the creation of complicated
|
|
multi-dimensional gaussian distributions. :mod:`lsqfit` supports
|
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Bayesian priors for the fit parameters, with arbitrarily
|
|
complicated multidimensional gaussian distributions. It uses
|
|
automatic differentiation to compute gradients, greatly simplifying
|
|
the design of fit functions.
|