Search Packages

dfo-ls

Python-based Derivative-Free Optimizer for Least-Squares

pyneqsys

Solve symbolically defined systems of non-linear equations numerically.

xcsf

XCSF learning classifier system: rule-based evolutionary machine learning

lsq-ellipse

Fitting an Ellipse using a Least Squares method, in Python

symfit

Symbolic Fitting; fitting as it should be.

pyclsp

A modular two-step convex optimization estimator for ill-posed problems

wlsqm

Fast and accurate weighted least squares meshless interpolator for Python

pytmpinv

Tabular Matrix Problems via Pseudoinverse Estimation

cvmatrix

Computation of training set (X^T * W * X) and (X^T * W * Y) or (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm and Jensen (2025).

hillfit

Fitting the Hill Equation to Experimental Data

lsqfitgp

A general purpose Gaussian process regression module

dfogn

DFO-GN: Derivative-Free Optimization using Gauss-Newton

regressionizer

Python package with a class that allows pipeline-like specification and execution of regression workflows.

fir1

FIR & LMS filter implementation in C++ with Python & JAVA wrappers

pylppinv

Linear Programming via Regularized Least Squares

equadratures

Polynomial approximations

tiny-solver

General factor graph solver in rust

py-minisam

No description available

pyfunctionbases

A Python module to compute multidimensional arrays of evaluated (orthogonal) functions.

jaxfit

GPU/TPU accelerated nonlinear least-squares curve fitting using JAX

lppinv

Linear Programming via Regularized Least Squares

pyrobustregressionlib

A library that implements algorithms for linear and non-linear robust regression.

fitting-toolkit

A python package for modelling data with a high degree of flexibillity and control.

mmq-high-precision

Solução robusta para o Método dos Mínimos Quadrados em Python. Projetada para ajustar polinômios de grau alto (10+) sem divergência. Integra aritmética de precisão infinita, correção automática para falta de dados e estabilização de matrizes mal-condicionadas. Ideal para modelagem matemática onde o NumPy padrão falha por erros de arredondamento.