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r-manipulatewidget
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public |
Like package 'manipulate' does for static graphics, this package helps to easily add controls like sliders, pickers, checkboxes, etc. that can be used to modify the input data or the parameters of an interactive chart created with package 'htmlwidgets'.
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2025-03-25 |
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r-leaflet
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public |
Create and customize interactive maps using the 'Leaflet' JavaScript library and the 'htmlwidgets' package. These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.
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2025-03-25 |
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r-lava.tobit
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Lava plugin allowing combinations of left and right censored and binary outcomes.
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2025-03-25 |
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r-labelled
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Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.
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2025-03-25 |
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r-janitor
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The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.
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2025-03-25 |
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r-ggpubr
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The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
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2025-03-25 |
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r-ggfortify
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Unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using 'ggplot2'.
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2025-03-25 |
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r-fuzzyjoin
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Join tables together based not on whether columns match exactly, but whether they are similar by some comparison. Implementations include string distance and regular expression matching.
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2025-03-25 |
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r-dt
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Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
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2025-03-25 |
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r-diagrammer
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Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
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2025-03-25 |
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r-dendextend
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Offers a set of functions for extending 'dendrogram' objects in R, letting you visualize and compare trees of 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different 'dendrograms' to one another.
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2025-03-25 |
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r-colourpicker
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A colour picker that can be used as an input in Shiny apps or Rmarkdown documents. The colour picker supports alpha opacity, custom colour palettes, and many more options. A Plot Colour Helper tool is available as an RStudio Addin, which helps you pick colours to use in your plots. A more generic Colour Picker RStudio Addin is also provided to let you select colours to use in your R code.
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2025-03-25 |
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r-broom
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Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
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2025-03-25 |
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r-bayesplot
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public |
Plotting functions for posterior analysis, prior and posterior predictive checks, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.
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2025-03-25 |
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r-tsibble
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public |
Provides a 'tbl_ts' class (the 'tsibble') to store and manage temporal data in a data-centric format, which is built on top of the 'tibble'. The 'tsibble' aims at easily manipulating and analysing temporal data, including counting and filling in time gaps, aggregate over calendar periods, performing rolling window calculations, and etc.
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2025-03-25 |
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r-tidygraph
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A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.
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2025-03-25 |
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r-sem
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Functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.
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2025-03-25 |
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r-sarima
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Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated.
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2025-03-25 |
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r-relevent
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Tools to fit relational event models.
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2025-03-25 |
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r-pdp
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A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.
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2025-03-25 |
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r-party
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A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available. The methods are described in Hothorn et al. (2006) <doi:10.1198/106186006X133933>, Zeileis et al. (2008) <doi:10.1198/106186008X319331> and Strobl et al. (2007) <doi:10.1186/1471-2105-8-25>.
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2025-03-25 |
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r-orientr
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This package provides a bare-bones interface to OrientDB's REST API. The package is currently limited to querying, but will eventually cover commands and batches in the future.
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2025-03-25 |
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r-latentnet
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Fit and simulate latent position and cluster models for statistical networks.
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2025-03-25 |
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r-ipumsr
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An easy way to import census, survey and geographic data provided by 'IPUMS' into R plus tools to help use the associated metadata to make analysis easier. 'IPUMS' data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from our website <https://ipums.org>.
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2025-03-25 |
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r-hmisc
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Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, and recoding variables.
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2025-03-25 |
