Error Propagation topic
Error (or uncertainty) propagation is the practice of analyzing and accounting for the effect of numeric quantities' uncertainties on the results of functions that involve them.
When variables used in a function or mathematical operation have errors (due to measurement uncertainties, random fluctuations, sample variance, etc.), error propagation can be used to determine the resulting error of the function's output.
MonteCarloMeasurements.jl
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
Measurements.jl
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical inte...
uncertainties
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
MetroloPy
Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure
jacobi
Numerical derivatives for Python
pyerrors
Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
errors
Uncertainty Propagation for R Vectors
BayesHistogram.jl
pure Julia package for optimal histogram binning, based on piecewise constant model.
asymmetric_uncertainty
A package for handling numeric quantities with asymmetric uncertainties.