Package-level declarations
Types
Covariance matrix for
Maximum allowed number of iterations
Free parameters of the optimization
Specify the way to compute distance from point to the curve as DifferentiableExpression
Compute a wight of the point. The more the weight, the more impact this point will have on the fit. By default, uses Dispersion^-1
An optimizer based onf Fyodor Tkachev's quasi-optimal weights method. See the article.
A fit problem for X-Y-Yerr data. Also known as "least-squares" problem.
Functions
Fit given data with a model provided as an expression
Optimize given XY (least squares) problem using this function Optimizer. The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting possible weight dependency on the model and parameters.
Optimizes differentiable expression using specific optimizer form given startingPoint.