model-fitting

A lean C++ library for working with point cloud data

torchbearer: A model fitting library for PyTorch

Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.

SourceXtractor++, the next generation SExtractor

JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets

Python framework for multi-parameter optimization and evaluation of protein folding models

Course Project for the course CS 736

Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.

tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics

Implementation of the algorithm described in the following paper. Korenberg, M., Billings, S.A. and Liu, Y.P. (1987) An Orthogonal Parameter Estimation Algorithm for Nonlinear Stochastic Systems

An R package of S3 generic methods for Bayesian analyses that generate MCMC samples

This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.

Toolbox for change-point detection and ideal-observer analyses of IBL task data

GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga

General RANSAC solver with detailed examples.

Tutorial on Bayesian model fitting with (Py)VBMC.

Elegant Mathematica-style model manipulation, fitting and exploration in MATLAB.

a curvature descent optimisation routine for highly parameterised non-linear dynamical models

Visualization and model fitting for Kobe Bryant shots over the course of his career. Data comes from the Kobe Bryant Shot Selection Kaggle Competition