Search Results for "r-cran"
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Showing 2016 open source projects for "r-cran"
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a R package. 'Qair' gives access to data bases used by air quality monitoring associations in France. It also contains functions to manipualte air quality datas.
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timetools (for r-cran)
Seasonal/Sequential (Instants/Durations, Even or not) Time Series
Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : POSIXcti, POSIXctp, TimeIntervalDataFrame, TimeInstantDataFrame, SubtimeDataFrame ; methods to switch from a class to another and to modify the time support of series (hourly time... -
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'geoconv' is a package to use with R (r-cran). This package is made of functions to convert geographic coordinates and to project geographic coordinates.
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blavaan
An R package for Bayesian structural equation modeling
blavaan is a free, open-source R package for Bayesian latent variable analysis. It relies on JAGS and Stan to estimate models via MCMC. The blavaan functions and syntax are similar to lavaan. The development version of blavaan (containing updates not yet on CRAN) can be installed via the command provided in the documentation. Compilation is required; this may be a problem for users who currently rely on a binary version of blavaan from CRAN. -
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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. -
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rticles
LaTeX Journal Article Templates for R Markdown
An R package maintained by RStudio (now Posit) that supplies journal-specific R Markdown output formats and article templates to generate formatted LaTeX/PDF submissions across academic publishers. -
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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. -
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RStudio
RStudio is an integrated development environment (IDE) for R
...In addition to code editing and execution, RStudio offers extensive support for reproducible research via R Markdown, notebooks, and integration with version control systems like Git and SVN. Package development is built in, with tooling for building, checking, and testing R packages, plus integration with documentation tools, CRAN submission workflows, and project templates. -
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R Source
Read-only mirror of R source code
The wch/r-source repository is a read-only mirror of the official R language source code, maintained to reflect the upstream Subversion (SVN) R core development tree. This mirror provides public visibility into R’s internals—everything from the interpreter, base and recommended packages, documentation, and C/Fortran code under the hood. It is updated hourly to stay in sync with the upstream SVN. -
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R-KV
Redundancy-aware KV Cache Compression for Reasoning Models
R-KV introduces a method for compressing the KV cache during decoding, allowing models to maintain reasoning performance while reducing memory consumption and computational overhead. The approach focuses on identifying which attention heads and cache components are most important for maintaining reasoning quality, allowing less critical information to be compressed or discarded. -
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gt R
Easily generate information-rich, publication-quality tables from R
...Finally, the table is rendered by printing it at the console, including it in an R Markdown document, or exporting it to a file using gtsave(). Currently, gt supports the HTML, LaTeX, and RTF output formats. -
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esquisse
RStudio add-in to make plots interactively with ggplot2
The purpose of this add-in is to let you explore your data quickly to extract the information they hold. You can create visualization with {ggplot2}, filter data with {dplyr} and retrieve generated code. This addin allows you to interactively explore your data by visualizing it with the ggplot2 package. It allows you to draw bar plots, curves, scatter plots, histograms, boxplot and sf objects, then export the graph or retrieve the code to reproduce the graph. This addin allows you to... -
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httr
httr: a friendly http package for R
httr is superseded: only changes necessary to keep it on CRAN will be made. We recommend using httr2 instead. The aim of httr is to provide a wrapper for the curl package, customized to the demands of modern web APIs. Functions for the most important http verbs: GET(), HEAD(), PATCH(), PUT(), DELETE() and POST(). Automatic connection sharing across requests to the same website (by default, curl handles are managed automatically), cookies are maintained across requests, and an up-to-date root-level SSL certificate store is used. ... -
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R.swift
Autocompleted resources like images, fonts & segues in Swift projects
...Autocompleted, never have to guess that image name again. For autocompleted images, and compiletime checked images. After installing R.swift into your project you can use the R-struct to access resources. If the struct is outdated just build and R.swift will correct any missing/changed/added resources. Runtime validation with R.validate() ff all images used in storyboards and nibs are available, if all named colors used in storyboards and nibs are available, if all view controllers with storyboard identifiers can be loaded, if all custom fonts can be loaded. -
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psychmeta
Psychometric meta-analysis toolkit
...Currently, the package supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Please refer to the overview tutorial vignette for an introduction to psychmeta’s functions and workflows. psychmeta is hosted on both CRAN and GitHub. Documentation for psychmeta’s functions is available in the package’s PDF manual. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. -
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Mesh R-CNN
code for Mesh R-CNN, ICCV 2019
Mesh R-CNN is a 3D reconstruction and object understanding framework developed by Facebook Research that extends Mask R-CNN into the 3D domain. Built on top of Detectron2 and PyTorch3D, Mesh R-CNN enables end-to-end 3D mesh prediction directly from single RGB images. The model learns to detect, segment, and reconstruct detailed 3D mesh representations of objects in natural images, bridging the gap between 2D perception and 3D understanding. -
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gganimate
A Grammar of Animated Graphics
...We define that when a box appears it should fade into view, whereas it should shrink away when it disappears. Lastly, we decide to use a sinusoidal easing for all our aesthetics (here, only y is changing) gganimate is available on CRAN and can be installed with install.packages('gganimate'). -
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R Color Palettes
Comprehensive list of color palettes available in R
This repository is a curated collection of color palettes crafted or curated for data visualization in R. The goal is to provide designers, data scientists, and R users with aesthetically pleasing, perceptually consistent color schemes that work well for plots, maps, and graphics. The repo contains static files listing palette definitions (e.g. hex codes, named hues), sample visualizations showing how each palette performs under different contexts (categorical, sequential, diverging), and helper functions/scripts to import or use the palettes in R. -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
...According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care. You can simply create spatial analytics and data mining applications and run them in any cloud environments. -
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grafify
A browser-based app (Windows) for graphs and ANOVAs (linear models).
This is a browser-based version of the R package grafify. It includes portable R and grafify as a Shiny package (Windows OS only). Get the R version from CRAN (https://cran.r-project.org/web/packages/grafify/index.html) or GitHub (https://github.com/ashenoy-cmbi/grafify) -
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rmarkdown
Dynamic Documents for R
R Markdown is an R package for creating dynamic, reproducible documents that combine code (R, Python, SQL, etc.), results (figures, tables), and narrative text. Built on Knitr and Pandoc, it supports generating HTML, PDF, Word, slideshows, dashboards, and more. It’s widely used in data science and reproducible reporting workflows. -
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rollama
Wrap the Ollama API, which allows you to run different LLMs
rollama is an R package that provides a convenient interface for interacting with local large language models through the Ollama API, bringing modern AI capabilities into the R ecosystem. It is designed to make LLM usage accessible to data scientists and researchers who work primarily in R, allowing them to generate text, analyze data, and create embeddings without relying on external cloud services. -
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plumber
Turn your R code into a web API
plumber is an R package that enables rapid creation of HTTP APIs by decorating existing R functions with special roxygen-style comments. It transforms R scripts into RESTful web services with minimal setup and integrates easily with RStudio or CI environments. -
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reticulate
R Interface to Python
reticulate is an R package from Posit that creates seamless interoperability between R and Python. It lets you call Python modules, classes, and functions from within R, automatically translating between R and Python data structures. Useful for combining Python tooling with R projects, data analysis, and RMarkdown reports. -
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JuliaConnectoR
A functionally oriented interface for calling Julia from R
This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R.
