
naniar - Data Structures, Summaries, and Visualisations for Missing Data
Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2023) <doi:10.18637/jss.v105.i07>.
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data-visualisationggplot2missing-datamissingnesstidy-data
15.30 score 672 stars 11 dependents 7.3k scripts 25k downloads
visdat - Preliminary Visualisation of Data
Create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using 'ggplot2'.
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exploratory-data-analysismissingnesspeer-reviewedropenscivisualisation
13.21 score 462 stars 12 dependents 2.7k scripts 24k downloads
visdat - Preliminary Visualisation of Data
Create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using 'ggplot2'.
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exploratory-data-analysismissingnesspeer-reviewedropenscivisualisation
13.21 score 462 stars 12 dependents 2.7k scripts 24k downloads
greta - Simple and 'Scalable' Statistical Modelling in R
Write statistical models in R and fit them by MCMC and optimisation on 'CPUs' and 'GPUs', using Google 'TensorFlow'. 'greta' lets you write your own model like in BUGS, JAGS and Stan, except that you write models right in R, it scales well to massive datasets, and it’s easy to extend and build on. See the website for more information, including tutorials, examples, package documentation, and the 'greta' forum.
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10.85 score 601 stars 4 dependents 516 scripts 79 downloads
geotargets - 'targets' Extensions for Geographic Spatial Formats
Provides extensions for various geographic spatial file formats, such as shape files and rasters. Currently provides support for the 'terra' geographic spatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.
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geospatialpipeliner-targetopiarasterreproducibilityreproducible-researchtargetsvectorworkflow
7.94 score 93 stars 116 scripts 610 downloadsconmat - Builds Contact Matrices using Generalised Additive Models (GAMs) and Population Data
Builds contact matrices using Generalised Additive Models (GAMs) and population data, as described in Tierney, Saraswati, Babu, Lydeamore, and Golding (2026) <doi:10.21105/joss.08326>. This package incorporates data that is copyright Commonwealth of Australia (Australian Electoral Commission and Australian Bureau of Statistics) 2020.
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contact-matricesinfectious-diseasespopulation-datapublic-health
7.54 score 21 stars 76 scripts
geotargets - 'targets' Extensions for Geographic Spatial Formats
Provides extensions for various geographic spatial file formats, such as shape files and rasters. Currently provides support for the 'terra' geographic spatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.
Last updated
geospatialpipeliner-targetopiarasterreproducibilityreproducible-researchtargetsvectorworkflow
7.24 score 93 stars 117 scripts 591 downloads
syn - Creates Synonyms From Target Words
Generates synonyms from a given word drawing from a synonym list from the 'moby' project <http://moby-thesaurus.org/>.
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antonymsozunconf18synonymstext-processingthesaurusunconf
6.41 score 54 stars 2 dependents 32 scripts 262 downloadsmaxcovr - A Set of Tools For Solving The Maximal Covering Location Problem
Solving the "maximal covering location problem" as described by Church can be difficult for users not familiar with linear programming. maxcovr provides functions to make it easy to solve this problem, and tools to calculate facility coverage.
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distancelinear-programmingcpp
5.89 score 46 stars 56 scriptsgreta.gp - Gaussian Process Modelling in 'greta'
Provides a syntax to create and combine Gaussian process kernels in 'greta'. You can then them to define either full rank or sparse Gaussian processes. This is an extension to the 'greta' software, Golding (2019) <doi:10.21105/joss.01601>.
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5.23 score 19 stars 45 scripts 57 downloadsmmcc - tidy mcmc.list using data.table
Tidy up, diagnose, and visualise your mcmc samples quickly and easily so you can get on with your analysis.
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4.64 score 22 stars 10 scriptsurbioconnect - Urban Habitat Connectivity Analysis
Analyse and visualise habitat connectivity in urban landscapes, accounting for barriers and buffer distances. Includes Shiny app for interactive analysis and report generation. Based on methods developed by Kirk et al (2023) <doi:10.1016/j.mex.2022.101989>.
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ecologyshinyspatial-analysisurban-ecologyquarto
4.43 score 12 scriptsgreta.dynamics - Modelling Structured Dynamical Systems in 'greta'
A 'greta' extension for analysing transition matrices and ordinary differential equations representing dynamical systems. Provides functions for analysing transition matrices by iteration, and solving ordinary differential equations. This is an extension to the 'greta' software, Golding (2019) <doi:10.21105/joss.01601>.
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4.33 score 6 stars 18 scripts 58 downloadsbroomstick - Convert Decision Tree Objects into Tidy Data Frames
Convert Decision Tree objects into tidy data frames, by using the framework laid out by the package broom, this means that decision tree output can be easily reshaped, porocessed, and combined with tools like 'dplyr', 'tidyr' and 'ggplot2'. Like the package broom, broomstick provides three S3 generics: tidy, to summarise decision tree specific features - tidy returns the variable importance table; augment adds columns to the original data such as predictions and residuals; and glance, which provides a one-row summary of model-level statistics.
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broomdecision-treesgbmmachine-learningrandomforestrpartstatistical-learning
3.61 score 29 stars 28 scriptsgreta.gam - Generalised Additive Models in 'greta' using 'mgcv'
A 'greta' (Golding (2019) <doi:10.21105/joss.01601>) module that lets you use 'mgcv' smoother functions and formula syntax to define smooth terms for use in a 'greta' model. You can then define your own likelihood to complete the model, and fit it by Markov Chain Monte Carlo (MCMC).
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3.34 score 11 stars 6 scripts 4 downloads