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mschauer/CausalInference.jl

Stars
183
Rank 202,994 (Top 5 %)
Language
Julia
License
Other
Created almost 7 years ago
Updated about 1 month ago

mschauer/CausalInference.jl

mschauer

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Causal inference, graphical models and structure learning in Julia

Causalinference.jl

Julia package for causal inference, graphical models and structure learning.

This package contains code for the stable version of the PC algorithm and the extended FCI algorithm.

See the documentation for implemented functionality and issue #1 (Roadmap/Contribution) for coordination of the development.

FAQ

Q: I looked for "causal inference" and found CausalInference.jl and Omega.jl... A: CausalInference.jl is about causal discovery; you observe the data and want to infer the causal structure. Omega lets you reason what happens then: when you intervene ("do calculus") and want to cause changes.

Bridge.jl

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Jupyter Notebook

ZigZagBoomerang.jl

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

Kalman.jl

Flexible filtering and smoothing in Julia

Mitosis.jl

Automatic probabilistic programming for scientific machine learning and dynamical models

DynamicIterators.jl

Iterators with message passing and feedback loops

GaussianDistributions.jl

Gaussian distributions as state variables and for uncertainty quantification with Unitful

GoldenSequences.jl

Generalized golden sequences, a form of low discrepancy sequence or quasi random numbers

MitosisStochasticDiffEq.jl

Backward-filtering forward-guiding with StochasticDiffEq.jl

PointProcessInference.jl

Statistical inference for Poisson Processes

MicrostructureNoise.jl

Nonparametric Bayesian volatility learning under microstructure noise

Jupyter Notebook

Trajectories.jl

Maps from the line into spaces

IDRsSolver.jl

++ incorporated into https://github.com/JuliaLang/IterativeSolvers.jl ++ Induced Dimension Reduction method IDR(s) for solving general non-symmetric linear equations using a Krylov method, for example ordinary linear equations or Sylvester and Stein equations.

BridgeLandmarks.jl

Image analysis and stochastic processes on shape and landmark spaces.

BayesEstDiffusion.jl

Code accompanying the paper Frank van der Meulen, Moritz Schauer: Bayesian estimation of discretely observed multi-dimensional diffusion processes using guided proposals

SDE.jl

This package is obsoleted by https://github.com/mschauer/Bridge.jl

nonparbayes

Tour through non-parametric Bayesian regression in Fourier domain using Julia https://mschauer.github.io/nonparbayes/

BridgeSPDE.jl

Stochastic partial differential equations with Bridge.jl

StructuresSeminar

Statistics for Structures Seminar

Schauder.jl

A graphical perspective on Gauss-Markov process priors and fast sparse Cholesky for hierarchically structured (generalized arrow) matrices

FingerTrees.jl

The persistent data structure Finger Tree in Julia