Showing 13 open source projects for "statistics"

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  • 1
    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
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  • 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...
    Downloads: 0 This Week
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  • 3
    forecast

    forecast

    Forecasting Functions for Time Series and Linear Models

    ...It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc.
    Downloads: 0 This Week
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  • 4
    clusterProfiler

    clusterProfiler

    A universal enrichment tool for interpreting omics data

    clusterProfiler is an R/Bioconductor package that provides a unified workflow for functional enrichment analysis to interpret high-throughput omics results. It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. ...
    Downloads: 0 This Week
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  • 5
    targets

    targets

    Function-oriented Make-like declarative workflows for R

    The targets package is a pipeline / workflow management tool in R, designed to coordinate multi‐step computational workflows in data science / statistics. It tracks dependencies between “targets” (computational steps), skips steps whose upstream data or code hasn’t changed, supports parallel computation, branching (dynamic generation of sub‐targets), file format abstractions, and encourages reproducible and efficient analyses. It’s something like GNU Make for R, but more integrated. ...
    Downloads: 0 This Week
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  • 6
    LabPlot

    LabPlot

    Data Visualization and Analysis

    LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
    Downloads: 21 This Week
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  • 7
    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
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  • 8
    Statistics for Data Scientists

    Statistics for Data Scientists

    "Statistics for Data Scientists: 50 Essential Concepts"

    The “statistics-for-data-scientists” repository is a pedagogical resource designed to bridge rigorous statistics theory and practical data science workflows. The code and materials are intended to help data scientists and analysts grasp statistical principles (e.g. inference, regressions, hypothesis testing, probability, confidence intervals) in contexts relevant to real data analysis tasks.
    Downloads: 0 This Week
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  • 9
    stat-cookbook

    stat-cookbook

    The probability and statistics cookbook

    A compact “Probability and Statistics Cookbook” offering concise mathematical recipes for key statistical concepts—expectation, variance, distributions and inequalities—packaged as LaTeX and R-based executable documents.
    Downloads: 0 This Week
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  • 10
    swirl

    swirl

    Learn R, in R

    swirl is an R package that allows interactive, in-R learning of statistics, data science, R programming etc. The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc.
    Downloads: 0 This Week
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  • 11
    Open Intro Statistics

    Open Intro Statistics

    An open-source textbook written at the college level

    OpenIntro Statistics is a dynamic take on the traditional curriculum, being successfully used at Community Colleges to the Ivy League. Each chapter's content is in one of the eight chapter folders that start with "ch_". Within each folder, there is a "figures" folder and a "TeX" folder. The TeX folder contains the text files that are used to typeset the chapters in the textbook.
    Downloads: 0 This Week
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  • 12
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    ...By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.
    Downloads: 4 This Week
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  • 13
    RStan

    RStan

    RStan, the R interface to Stan

    ...RStan integrates with Stan’s automatic differentiation library, provides diagnostics, model comparison, posterior predictive checks, etc. It is used in research, applied statistics, and modelling workflows where flexibility and rigor in Bayesian methods are required.
    Downloads: 0 This Week
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