Showing 11 open source projects for "statistical"

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  • 1
    Mixed-effects models in Julia

    Mixed-effects models in Julia

    A Julia package for fitting (statistical) mixed-effects models

    This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using Treatment 1 versus the placebo". ...
    Downloads: 2 This Week
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  • 2
    GLM.jl

    GLM.jl

    Generalized linear models in Julia

    GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. @formula) and matrix-based interfaces, allowing both high-level convenience and low-level control. ...
    Downloads: 0 This Week
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  • 3
    RCall.jl

    RCall.jl

    Call R from Julia

    R is a language for statistical computing and graphics that has been around for a couple of decades and it has one of the most impressive collections of scientific and statistical packages of any environment. Recently, the Julia language has become an attractive alternative because it provides the remarkable performance of a low-level language without sacrificing the readability and ease of use of high-level languages.
    Downloads: 0 This Week
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  • 4
    Compose.jl

    Compose.jl

    Declarative vector graphics

    Compose is a vector graphics library for Julia. It forms the basis for the statistical graphics system Gadfly. Compose is a declarative vector graphics system written in Julia. It's designed to simplify the creation of complex graphics and serves as the basis of the Gadfly data visualization package.
    Downloads: 0 This Week
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  • 5
    Bayesian Statistics

    Bayesian Statistics

    This repository holds slides and code for a full Bayesian statistics

    This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. ...
    Downloads: 0 This Week
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  • 6
    Bootstrap.jl

    Bootstrap.jl

    Statistical bootstrapping library for Julia

    Bootstrapping is a widely applicable technique for statistical estimation.
    Downloads: 0 This Week
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  • 7
    Bayesian Julia

    Bayesian Julia

    Bayesian Statistics using Julia and Turing

    Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. ...
    Downloads: 0 This Week
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  • 8
    MeasureTheory.jl

    MeasureTheory.jl

    "Distributions" that might not add to one.

    Probabilistic programming and statistical computing are vibrant areas in the development of the Julia programming language, but the underlying infrastructure dramatically predates recent developments. The goal of MeasureTheory.jl is to provide Julia with the right vocabulary and tools for these tasks. In this package we introduce well-chosen foundational primitives centered around the notion of measure, density and conditional probability with powerful combinators and transforms intended to power and unify work on probabilistic programming and statistical computing within Julia. ...
    Downloads: 0 This Week
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  • 9
    Gadfly

    Gadfly

    Crafty statistical graphics for Julia

    Gadfly is a system for plotting and visualization written in Julia. It is based largely on Hadley Wickhams's ggplot2 for R and Leland Wilkinson's book The Grammar of Graphics. It was Daniel C. Jones' brainchild and is now maintained by the community.
    Downloads: 0 This Week
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  • 10
    Bridge.jl

    Bridge.jl

    A statistical toolbox for diffusion processes

    Statistics and stochastic calculus for Markov processes in continuous time, include univariate and multivariate stochastic processes such as stochastic differential equations or diffusions (SDE's) or Levy processes.
    Downloads: 0 This Week
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  • 11
    Stats With Julia Book

    Stats With Julia Book

    Collection of runnable Julia code examples for a statistics book

    ...The repository is designed for Julia users and provides ready-to-run examples that reinforce theoretical concepts with practical implementation. Readers can explore how Julia supports statistical modeling, simulation, and computational methods in data science workflows. The included initialization script simplifies package setup, ensuring that learners can focus on running and modifying the code examples. This project bridges the gap between textbook learning and hands-on coding, making it a valuable educational tool for students, researchers, and practitioners.
    Downloads: 6 This Week
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