Showing 16 open source projects for "bns-tools"

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  • 1
    easystats

    easystats

    The R easystats-project

    easystats is a meta‑package that installs and unifies a suite of R packages for post‑processing statistical models. It delivers a consistent API to assess model performance, effect sizes, parameters, and to generate reports and visualizations, all with minimal dependencies and maximum clarity.
    Downloads: 0 This Week
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  • 2
    RStudio Cheatsheets

    RStudio Cheatsheets

    Curated collection of official cheat sheets for data science tools

    The cheatsheets repository from RStudio is a curated collection of official cheat sheets for R, RStudio, the tidyverse, Shiny, and related data science tools. Each cheat sheet is a single (or double) page PDF that condenses important syntax, functions, workflows, and best practices into a visually organized format ideal for quick reference. The repository contains source files (R Markdown or LaTeX) that generate the cheat sheets, version history, and metadata (title, author, description) for each. ...
    Downloads: 2 This Week
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  • 3
    Awesome Network Analysis

    Awesome Network Analysis

    A curated list of awesome network analysis resources

    awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data.
    Downloads: 1 This Week
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  • 4
    dplyr

    dplyr

    dplyr: A grammar of data manipulation

    dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows.
    Downloads: 5 This Week
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  • 5
    devtools

    devtools

    Tools to make an R developer's life easier

    devtools is an R package designed to simplify R package development by providing functions for creating, building, testing, and installing packages from various sources (e.g., CRAN, GitHub). It integrates with usethis, roxygen2, testthat, and simplifies workflows for developers and contributors to the R ecosystem.
    Downloads: 1 This Week
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  • 6
    purrr

    purrr

    A functional programming toolkit for R

    purrr enhances R’s functional programming capabilities by providing a consistent set of tools for working with lists and vectors, enabling safer and more expressive iteration compared to base R’s loop functions.
    Downloads: 0 This Week
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  • 7
    golem

    golem

    A Framework for Building Robust Shiny Apps

    golem is an opinionated framework for developing production-grade Shiny applications in R, treating the app like a full R package. It scaffolds project structure, testing, documentation, CI/CD, and supports containerization—streamlining the build-to-deploy pipeline while enforcing clean architecture and maintainability.
    Downloads: 0 This Week
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  • 8
    performance

    performance

    Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

    performance is part of the easystats ecosystem and offers model quality assessment tools for R. It computes metrics like R², RMSE, ICC, and conducts diagnostics such as overdispersion, zero‑inflation, convergence, and singularity checks, complementing model workflows with comprehensive evaluation.
    Downloads: 0 This Week
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  • 9
    gptstudio

    gptstudio

    GPT RStudio addins that enable GPT assisted coding, writing & analysis

    gptstudio is an R package and RStudio Addins interface that enables interactive use of large language models (OpenAI, HuggingFace, etc.) from within R. It includes a Chat add-in and source editing helpers to query models, generate code, comment or refactor code, and manage conversations—all integrated into RStudio using Shiny and bslib.
    Downloads: 0 This Week
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  • 10
    blogdown

    blogdown

    Create Blogs and Websites with R Markdown

    blogdown is an R package that enables the creation and maintenance of static websites and blogs using R Markdown and Hugo (or other static-site generators). Developed by Yihui Xie and team, it provides functions to initialize sites, write posts, manage themes, and deploy with minimal fuss. It seamlessly blends R code chunks and web content, ideal for data storytellers and technical bloggers.
    Downloads: 0 This Week
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  • 11
    plotly

    plotly

    An interactive graphing library for R

    ...Moreover, both approaches are an implementation of the Grammar of Graphics and both are powered by the JavaScript graphing library plotly.js, so many of the same concepts and tools that you learn for one interface can be reused in the other. Any graph made with the plotly R package is powered by the JavaScript library plotly.js. The plot_ly() function provides a ‘direct’ interface to plotly.js with some additional abstractions to help reduce typing.
    Downloads: 0 This Week
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  • 12
    Statistical Rethinking 2024

    Statistical Rethinking 2024

    This course teaches data analysis

    ...The 2024 repo also highlights the transition toward more robust Stan models and integration with newer Bayesian workflow practices, continuing to emphasize accessibility for learners while modernizing the tools. This version is designed for students following the 2024 lecture series, offering the most current set of examples, exercises, and teaching material aligned with the Statistical Rethinking framework. Online, flipped instruction. I will pre-record the lectures each week. We'll meet online once a week for an hour to discuss the material. ...
    Downloads: 2 This Week
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  • 13
    Statistical Rethinking 2023

    Statistical Rethinking 2023

    Statistical Rethinking Course for Jan-Mar 2023

    The 2023 edition modernizes and expands on the same curriculum, adjusting exercises and code for newer versions of R, Stan, and supporting packages. It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following...
    Downloads: 0 This Week
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  • 14
    R Packages (r-pkgs)

    R Packages (r-pkgs)

    Building R packages

    rpkgs (in GitHub via hadley/r-pkgs) is the source (text + examples) for the book R Packages by Hadley Wickham and Jenny Bryan. The book teaches how to develop, document, test, and share R packages: the practices, tools, infrastructure, workflows, and best practices around package development in R. The repository contains the code, text, site content for building the book, examples, exercises, etc. It is not a software library to be loaded in R (except perhaps the examples), but a resource/guide/manual. The first edition is no longer available online. ...
    Downloads: 0 This Week
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  • 15
    Reproducible-research

    Reproducible-research

    A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.

    In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. ...
    Downloads: 0 This Week
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  • 16
    benchm-ml

    benchm-ml

    A benchmark of commonly used open source implementations

    This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different...
    Downloads: 0 This Week
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