Adds a new keyword linear to lsqfit.nonlinear_fit(...) that lists (optionally) which fit parameters appear linearly in the fit function. These parameters are removed from the fit using variable projection and then restored afterwards
Adds new class lsqfit.MultiFitter. This provides a framework for organizing complex fits around a sm...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Removes the extend parameter from lsqfit.nonlinear_fit. That parameter is no longer necessary: the a...
Minor update: Setting p0=True causes nonlinear_fit() to choose the fit search's starting point at ra...
Minor bug fix for fit residuals. New diagnostic tools for examining fit residuals: eg, fit.qqplot_re...
This provides: a minor bug fix in lsqfit.MultiFitter.chained_fit concerning fit.svdcorrection; and a...
This version offers a major overhaul of the underlying fitting strategies used by lsqfit, featuring ...
Adds new keywords add_svdnoise and add_priornoise to help assess fit quality; see new sections on Go...
Removes lsqfit.BayesIntegrator (and BayesPDF) which is replaced by the more capable vegas.PDFIntegra...
Bug fix in lsqfit.wavg(...) for problem that was having an adverse effect on certain of lsqfit.Multi...
Introduces improved pickling which means that multiple processors (nproc>1) can be used when doing B...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Fixes a bug in empbayes_fit(z0, ...) that occurred when z0 was an integer or contained integers. Als...
Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Pyth...
Adds new class lsqfit.MultiFitter. This provides a framework for organizing complex fits around a sm...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Removes the extend parameter from lsqfit.nonlinear_fit. That parameter is no longer necessary: the a...
Minor update: Setting p0=True causes nonlinear_fit() to choose the fit search's starting point at ra...
Minor bug fix for fit residuals. New diagnostic tools for examining fit residuals: eg, fit.qqplot_re...
This provides: a minor bug fix in lsqfit.MultiFitter.chained_fit concerning fit.svdcorrection; and a...
This version offers a major overhaul of the underlying fitting strategies used by lsqfit, featuring ...
Adds new keywords add_svdnoise and add_priornoise to help assess fit quality; see new sections on Go...
Removes lsqfit.BayesIntegrator (and BayesPDF) which is replaced by the more capable vegas.PDFIntegra...
Bug fix in lsqfit.wavg(...) for problem that was having an adverse effect on certain of lsqfit.Multi...
Introduces improved pickling which means that multiple processors (nproc>1) can be used when doing B...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Fixes a bug in empbayes_fit(z0, ...) that occurred when z0 was an integer or contained integers. Als...
Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Pyth...
Adds new class lsqfit.MultiFitter. This provides a framework for organizing complex fits around a sm...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.lea...
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