This is a dimensionality reduction algorithm which has the goal of maintaining interpretability i.e we eliminate variables directly from potential models that don't seem to add any predictive power.

Computing the highest density region of a univariate, unimodal distribution in Julia

More zeros than you can shake a stick at

Explores representations based on bag words

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Simulating quantum computing verification

Virtual Age Models for Julia

Implementation of Asymptotic Numerical Method

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Common solvers within orbital mechanics and astrodynamics.

Julia wrapper for ABIDES-Markets

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Mirror of https://gitlab.kuleuven.be/numa/software/ApproximatingMapsBetweenLinearSpaces

Conduct one-way and multi-way anova in Julia with MixedModels.jl

Sampling from an unnormalized pdf in Julia using Walker's MCMC algorithm

A toolkit for progeny testing simulation

Build equations with informative errors for missing variables by explicitly assigning a process to each variable of the equations

Parameter estimation under uncertainty.

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Base package for JuliaPsychometricsBazaar ecosystem

Base package for JuliaPsychometricsBazaar ecosystem

Base data analysis methods for Paliquant

Python extensions relating to Caesar.jl

A thin wrapper around the python PyMBAR

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Julia wrapper for the Python Rhodium package

Postprocessing of data obtained by numerical simulations or measurements

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A package to handle data generated by QMSim