Search Results for "smith statistical package"
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Showing 9 open source projects for "smith statistical package"
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
{ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. -
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RCall.jl
Call R from Julia
...However, Julia still lacks the depth and scale of the R package environment. This package, RCall.jl, facilitates communication between these two languages and allows the user to call R packages from within Julia, providing the best of both worlds. Additionally, this is a pure Julia package so it is portable and easy to use. -
3
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. -
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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. -
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5
ggforce
Accelerating ggplot2
ggforce is an extension package for ggplot2 that introduces specialized statistical transforms, geoms, and layout utilities to enhance and complement the built-in ggplot2 offerings. It enables more advanced visualization techniques such as faceting enhancements, hulls, annotation marks, and novel layouts for network data and marked regions. -
6
ggpubr
'ggplot2' Based Publication Ready Plots
ggpubr is an R package that provides easy-to-use wrapper functions around ggplot2 to create publication-ready visualizations with minimal code. It streamlines plot creation for researchers and analysts, allowing features such as statistical annotation, theme customization, and plot arrangement with fewer lines of code. -
7
awesome-single-cell
Community-curated list of software packages and data resources
...Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address the statistical challenges of single cell RNA-seq. The package incorporates novel and established methods to provide a flexible framework to perform filtering, quality control, normalization, dimension reduction, clustering, differential expression and a wide-range of plotting. ... -
8
see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). ... -
9
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. ... -
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