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R Mathematics Software

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Browse free open source R Mathematics Software and projects below. Use the toggles on the left to filter open source R Mathematics Software by OS, license, language, programming language, and project status.

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    MongoDB Atlas runs apps anywhere

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  • 1
    LabPlot

    LabPlot

    Data Visualization and Analysis

    LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
    Downloads: 32 This Week
    Last Update:
    See Project
  • 2
    CausalImpact

    CausalImpact

    An R package for causal inference in time series

    The CausalImpact repository houses an R package that implements causal inference in time series using Bayesian structural time series models. Its goal is to estimate the effect of an intervention (e.g. a marketing campaign, policy change) on a time series outcome by predicting what would have happened in a counterfactual “no intervention” world. The package requires as input a response time series plus one or more control (covariate) time series that are assumed unaffected by the intervention, and it divides the time horizon into “pre-intervention” and “post-intervention” periods. It uses Bayesian modeling to fit a structural time series to the pre-period and extrapolate a counterfactual prediction for the post period, then compares observed vs predicted to infer the causal effect. The package supports plotting, summary tables, and verbal narratives for interpretive reports.
    Downloads: 0 This Week
    Last Update:
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  • 3
    broom

    broom

    Convert statistical analysis objects from R into tidy format

    broom is part of the tidymodels ecosystem that converts statistical model outputs (e.g. from lm, glm, t.test, lme4, etc.) into tidy tibbles — standardized data frames — using functions tidy(), glance(), and augment(). These are easier to manipulate, visualize, and report programmatically.
    Downloads: 0 This Week
    Last Update:
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  • 4
    rethinking

    rethinking

    Statistical Rethinking course and book package

    This R package accompanies Richard McElreath’s Statistical Rethinking (2nd edition), offering utilities to fit and compare Bayesian models using both MAP estimation (quap) and Hamiltonian Monte Carlo via RStan (ulam). It supports specifying models via explicit distributional assumptions, providing flexibility for advanced statistical workflows.
    Downloads: 0 This Week
    Last Update:
    See Project
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