<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/august-2018-top-40-new-packages/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://rviews.rstudio.com/2018/09/26/august-2018-top-40-new-packages/"> R Views</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Package developers relaxed a bit in August.; only 160 new packages went to CRAN that month. Here are my “Top 40” picks organized into seven categories: Data, Machine Learning, Science, Statistics, Time Series, Utilities, and Visualization.</p>
<h3>Data</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=nsapi" target="_blank">nsapi</a> v0.1.1: Provides an interface to the <a rel="nofollow" href="https://www.ns.nl/en/travel-information/ns-api" target="_blank">Nederlandse Spoorwegen (Dutch Railways) API</a>, allowing users to download current departure times, disruptions and engineering work, the station list, and travel recommendations from station to station. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/nsapi/vignettes/basic_use_nsapi_package.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=repec" target="_blank">repec</a> v0.1.0: Provides utilities for accessing <a rel="nofollow" href="http://repec.org/" target="_blank">RePEc</a> (Research Papers in Economics) through a RESTful API. You can request an access code and get detailed information <a rel="nofollow" href="https://ideas.repec.org/api.html" target="_blank">here</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=rfacebookstat" target="_blank">rfacebookstat</a> v1.8.3: Implements an interface to the <a rel="nofollow" href="https://developers.facebook.com/docs/marketing-apis/" target="_blank">Facebook Marketing API</a>, allowing users to load data by campaigns, ads, ad sets, and insights.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=UCSCXenaTools" target="_blank">UCSCXenaTools</a> v0.2.4: Provides access to data sets from <a rel="nofollow" href="https://xena.ucsc.edu/public-hubs/" target="_blank">UCSC Xena data hubs</a>, which are a collection of UCSC-hosted public databases.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=ZipRadius" target="_blank">ZipRadius</a> v1.0.1: Generates a data frame of US zip codes and their distance to the given zip code, when given a starting zip code and a radius in miles. Also includes functions for use with <code>choroplethrZip</code>, which are detailed in the <a rel="nofollow" href="https://cran.r-project.org/web/packages/ZipRadius/vignettes/ZipRadius.html" target="_blank">vignette</a>.<br>
<img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/ZipRadius.png?w=450&ssl=1" data-recalc-dims="1" height="500"></p>
<h3>Machine Learning</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=dials" target="_blank">dials</a> v0.0.1: Provides tools for creating model parameters that cannot be directly estimated from the data. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/dials/vignettes/Basics.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tosca" target="_blank">tosca</a> v0.1-2: Provides a framework for statistical analysis in content analysis. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/tosca/vignettes/Vignette.pdf" target="_blank">vignette</a> for details.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/tosca.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tsmp" target="_blank">tsmap</a> v0.3.1: Implements the <a rel="nofollow" href="http://www.cs.ucr.edu/~eamonn/MatrixProfile.html" target="_blank">Matrix Profile concept</a> for classification.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/tsmap.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<h3>Science</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DSAIRM" target="_blank">DSAIRM</a> v0.4.0: Provides a collection of <code>Shiny</code> apps that implement dynamical systems simulations to explore within-host immune response scenarios. See the package <a rel="nofollow" href="https://cran.r-project.org/web/packages/DSAIRM/vignettes/DSAIRM.html" target="_blank">Tutorial</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=epiflows" target="_blank">epiflows</a> v0.2.0: Provides functions and classes designed to handle and visualize epidemiological flows between locations, as well as a statistical method for predicting disease spread from flow data initially described in <a rel="nofollow" href="doi:10.2807/1560-7917.ES.2017.22.28.30572" target="_blank">Dorigatti et al. (2017)</a>. For more information, see the <a rel="nofollow" href="http://www.repidemicsconsortium.org/" target="_blank">RECON toolkit</a> for outbreak analysis. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/epiflows/vignettes/introduction.html" target="_blank">Overview</a> and a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/epiflows/vignettes/epiflows-class.html" target="_blank">Data Preparation</a>.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/epiflows.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=fieldRS" target="_blank">fieldRS</a> v0.1.1: Provides functions for remote-sensing field work using best practices suggested by <a rel="nofollow" href="doi:10.1016/j.rse.2014.02.015" target="_blank">Olofsson et al. (2014)</a>. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/fieldRS/vignettes/fieldRS.html" target="_blank">vignette</a> for details.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/fieldsRS.png?w=450&ssl=1" data-recalc-dims="1" height="500"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=Rnmr1D" target="_blank">Rnmr1D</a> v1.2.1: Provides functions to perform the complete processing of proton nuclear magnetic resonance spectra from the free induction decay raw data. For details see <a rel="nofollow" href="doi:10.1007/s11306-017-1178-y" target="_blank">Jacob et al. (2017)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/Rnmr1D/vignettes/Rnmr1D.html" target="_blank">vignette</a>.</p>
<p><img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/Rnmr1D.png?w=450&ssl=1" data-recalc-dims="1" height="500"></p>
<h3>Statistics</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=bcaboot" target="_blank">bcaboot</a> v0.2-1: Provides functions to compute bootstrap confidence intervals in an almost automatic fashion. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/bcaboot/vignettes/bcaboot.html" target="_blank">vignette</a>.</p>
<p><img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/bcaboot.png?w=450&ssl=1" data-recalc-dims="1" height="500"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=bivariate" target="_blank">bivariate</a> v0.2.2: Contains convenience functions for constructing and plotting bivariate probability distributions. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/bivariate/vignettes/bivariate.pdf" target="_blank">vignette</a> for details.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/bivariate.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DesignLibrary" target="_blank">DesignLibrary</a> v0.1.1: Provides a simple interface to build designs and allow users to compare performance of a given design across a range of combinations of parameters, such as effect size, sample size, and assignment probabilities. Look <a rel="nofollow" href="https://declaredesign.org/library/" target="_blank">here</a> for more information.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=doremi" target="_blank">doremi</a> v0.1.0: Provides functions to fit the dynamics of a regulated system experiencing exogenous inputs using differential equations and linear mixed-effects regressions to estimate the characteristic parameters of the equation. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/doremi/vignettes/Introduction-to-doremi.html" target="_blank">vignette</a>.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/doremi.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=eikosograms" target="_blank">eikosograms</a> v0.1.1: An eikosogram (probability picture from the ancient Greek εὶκὀσ – likely or probable) divides the unit square into rectangular regions whose areas, sides, and widths represent various probabilities associated with the values of one or more categorical variates. For a discussion on the eikosogram and its superiority to Venn diagrams in teaching probability, see <a rel="nofollow" href="https://math.uwaterloo.ca/~rwoldfor/papers/eikosograms/paper.pdf" target="_blank">Cherry and Oldford (2003)</a>, and for a discussion of its value in exploring conditional independence structure and relation to graphical and log-linear models, see <a rel="nofollow" href="https://math.uwaterloo.ca/~rwoldfor/papers/eikosograms/independence/paper.pdf" target="_blank">Oldford (2003)</a>. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/eikosograms/vignettes/Introduction.html" target="_blank">Introduction</a> and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/eikosograms/vignettes/DataAnalysis.html" target="_blank">Data Analysis</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/eikosograms/vignettes/IndependenceExploration.html" target="_blank">Independence Relations</a>.</p>
<p><img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/eikosograms.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=localIV" target="_blank">localIV</a> v0.1.0: Provides functions to estimate marginal treatment effects using local instrumental variables. See <a rel="nofollow" href="doi:10.1162/rest.88.3.389" target="_blank">Heckman et al. (2006)</a> and <a rel="nofollow" href="https://scholar.harvard.edu/files/xzhou/files/zhou-xie_mte2.pdf" target="_blank">Zhou and Xie (2018)</a> for background.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=merlin" target="_blank">merlin</a> v0.0.1: Provides functions to fit linear, non-linear, and user-defined mixed effects regression models following the framework developed by <a rel="nofollow" href="arxiv:1710.02223" target="_blank">Crowther (2017)</a>. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/merlin/vignettes/merlin.html" target="_blank">vignette</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=MRFcov" target="_blank">MRFcov</a> v1.0.35: Provides functions to approximate node interaction parameters of Markov Random Fields graphical networks. The general methods are described in <a rel="nofollow" href="doi:10.1002/ecy.2221" target="_blank">Clark et al. (2018)</a>. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/MRFcov/vignettes/CRF_data_prep.html" target="_blank">Preparing Datasets</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/MRFcov/vignettes/Gaussian_Poisson_CRFs.html" target="_blank">Gaussian and Poisson Fields</a>, and an example using <a rel="nofollow" href="https://cran.r-project.org/web/packages/MRFcov/vignettes/Bird_Parasite_CRF.html" target="_blank">Bird parasite data</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SCPME" target="_blank">SCPME</a> v1.0: Provides functions to estimate a penalized precision matrix via an augmented ADMM algorithm as described in <a rel="nofollow" href="doi:10.1093/biomet/asy023" target="_blank">Molstad and Rothman (2018)</a>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/SCPME/vignettes/Tutorial.html" target="_blank">Tutorial</a> and a vignette describing <a rel="nofollow" href="https://cran.r-project.org/web/packages/SCPME/vignettes/Details.html" target="_blank">Algorithm Details</a>.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/SCPME.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=survxai" target="_blank">survxai</a> v0.2.0: Contains functions for creating a unified representation of survival models, which can be further processed by various survival explainers. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/survxai/vignettes/Local_explanations.html" target="_blank">Local explanations</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/survxai/vignettes/Global_explanations.html" target="_blank">global explanations</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/survxai/vignettes/How_to_compare_models_with_survxai.html" target="_blank">comparing models</a>, and on a <a rel="nofollow" href="https://cran.r-project.org/web/packages/survxai/vignettes/Custom_predict_for_survival_models.html" target="_blank">custom prediction function</a>.</p>
<p><img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/survxai.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<h3>Time Series</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=hpiR" target="_blank">hpiR</a> v0.2.0: Provides functions to compute house price indexes and series, and evaluate index goodness based on accuracy, volatility and revision statistics. For the background on model construction, see <a rel="nofollow" href="doi:10.2307/2109686" target="_blank">Case and Quigley (1991)</a>, and for hedonic pricing models, see <a rel="nofollow" href="doi:10.1016/j.jhe.2006.03.001" target="_blank">Bourassa et al. (2006)</a>. There is an an <a rel="nofollow" href="https://cran.r-project.org/web/packages/hpiR/vignettes/introduction.html" target="_blank">introduction</a> to the package and a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/hpiR/vignettes/classstructure.html" target="_blank">Classes</a>.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/hpiR.png?w=450&ssl=1" data-recalc-dims="1" height="500"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=STMotif" target="_blank">STMotif</a> v0.1.1: Provides functions to identify motifs (previously identified sub-sequences) in spatial-time series. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/STMotif/vignettes/discovery-motifs.html" target="_blank">motif discovery</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/STMotif/vignettes/examples.html" target="_blank">examples</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/STMotif/vignettes/generation-of-candidates.html" target="_blank">candidate generation</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/STMotif/vignettes/validate-candidates.html" target="_blank">candidate validation</a>.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/hpiR.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=trawl" target="_blank">trawl</a> v0.2.1: Contains functions for simulating and estimating integer-valued trawl processes as described in <a rel="nofollow" href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3100076" target="_blank">Veraart (2018)</a>, and for simulating random vectors from the bivariate negative binomial and the bi- and trivariate logarithmic series distributions. There is a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/trawl/vignettes/my-vignette2.html" target="_blank">trawl processes</a>, and another on the <a rel="nofollow" href="https://cran.r-project.org/web/packages/trawl/vignettes/my-vignette.html" target="_blank">binomial distributions</a>.</p>
<h3>Utilities</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/src/contrib/Archive/arkdb" target="_blank">arkdb</a> v0.0.3: Provides functions for exporting tables from relational database connections into compressed text files, and streaming those text files back into a database without requiring the whole table to fit in working memory. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/arkdb/vignettes/arkdb.html" target="_blank">vignette</a> for a tutorial.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=aws.kms" target="_blank">aws.kms</a> v0.1.2: Implements an interface to <a rel="nofollow" href="https://aws.amazon.com/kms/" target="_blank">AWS Key Management Service</a>, a cloud service for managing encryption keys. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/aws.kms/readme/README.html" target="_blank">README</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DataPackageR" target="_blank">DatapackageR</a> v0.15.3: Provides a framework to help construct R data packages in a reproducible manner. It maintains data provenance by turning the data-processing scripts into package vignettes, as well as enforcing documentation and version checking of included data objects. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/DataPackageR/vignettes/usingDataPackageR.html" target="_blank">Guide</a> to using the package, and a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/DataPackageR/vignettes/YAML_CONFIG.html" target="_blank">YAML configuration</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=hedgehog" target="_blank">hedgehog</a> v0.1: Enables users to test properties of their programs against randomly generated input, providing far superior test coverage compared to unit testing. There is a general <a rel="nofollow" href="https://cran.r-project.org/web/packages/hedgehog/vignettes/hedgehog.html" target="_blank">tutorial</a> and a description of the <a rel="nofollow" href="https://cran.r-project.org/web/packages/hedgehog/vignettes/state-machines.html" target="_blank">Hedgehog state machine</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=jsonstat" target="_blank">jsonstat</a> v0.0.2: Implements an interface to <a rel="nofollow" href="https://json-stat.org/" target="_blank">JSON-stat</a>, a simple, lightweight ‘JSON’ format for data dissemination. There is a short <a rel="nofollow" href="https://cran.r-project.org/web/packages/jsonstat/vignettes/quickstart.html" target="_blank">quickstart quide</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=nseval" target="_blank">nseval</a> v0.4: Provides an API for Lazy and Non-Standard Evaluation with facilities to capture, inspect, manipulate, and create lazy values (promises), “…” lists, and active calls. See <a rel="nofollow" href="https://cran.r-project.org/web/packages/nseval/readme/README.html" target="_blank">README</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=runner" target="_blank">runner</a> v0.1.0: Provides running functions (windowed, rolling, cumulative) with varying window size and missing handling options for R vectors. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/runner/vignettes/runner.html" target="_blank">vignette</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=RTest" target="_blank">RTest</a> v1.1.9.0: Provides an XML-based testing framework for automated component tests of R packages developed for a regulatory environment. There is a short <a rel="nofollow" href="https://cran.r-project.org/web/packages/RTest/vignettes/RTest.pdf" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=sparkbq" target="_blank">sparkbq</a> v0.1.0: Extends <code>sparklyr</code> by providing integration with Google <a rel="nofollow" href="https://cloud.google.com/bigquery/" target="_blank">BigQuery</a>. It supports direct import/export from/to <code>BigQuery</code>, as well as intermediate data extraction from <a rel="nofollow" href="https://cloud.google.com/storage/" target="_blank">Google Cloud Storage</a>. See <a rel="nofollow" href="https://cran.r-project.org/web/packages/sparkbq/readme/README.html" target="_blank">README</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=vapour" target="_blank">vapour</a> v0.1.0: Provides low-level access to <code>GDAL</code>, the <a rel="nofollow" href="http://gdal.org/" target="_blank">Geospatial Data Abstraction Library</a>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/vapour/vignettes/vapour.html" target="_blank">vignette</a>.</p>
<h3>Visualization</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=mapdeck" target="_blank">mapdeck</a> v0.1.0: Provides a mechanism to plot interactive maps using <a rel="nofollow" href="https://www.mapbox.com/mapbox-gl-js/api/" target="_blank">Mapbox GL</a>, a JavaScript library for interactive maps, and <a rel="nofollow" href="http://deck.gl/#/" target="_blank">Deck.gl</a>, a JavaScript library which uses <code>WebGL</code> for visualizing large data sets. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/mapdeck/vignettes/mapdeck.html" target="_blank">vignette</a> explains how to use the package.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/mapdeck.gif?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=rayshader" target="_blank">rayshader</a> v0.5.1: Provides functions that use a combination of raytracing, spherical texture mapping, lambertian reflectance, and ambient occlusion to produce hillshades of elevation matrices. Includes water-detection and layering functions, programmable color palette generation, built-in textures, 2D and 3D plotting options, and more. See <a rel="nofollow" href="https://cran.r-project.org/web/packages/rayshader/readme/README.html" target="_blank">README</a> for details and examples.</p>
<p><img src="https://i0.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/rayshader.gif?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=sigmajs" target="_blank">sigmajs</a> v0.1.1: Provides an interface to the <a rel="nofollow" href="http://sigmajs.org/" target="_blank">sigma.js</a> graph-visualization library, including animations, plugins, and shiny proxies. There is a brief <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/get_started.html" target="_blank">Get Started Guide</a>, and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/animate.html" target="_blank">Animation</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/buttons.html" target="_blank">Buttons</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/cluster.html" target="_blank">Coloring by Cluster</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/dynamic.html" target="_blank">Dynamic graphs</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/formats.html" target="_blank">igraph &amp; gexf</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/layout.html" target="_blank">Layout</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/plugins.html" target="_blank">Plugins</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/settings.html" target="_blank">Settings</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/shiny.html" target="_blank">Shiny</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/sigmajs/vignettes/talkcross.html" target="_blank">Crosstalk</a>.</p>
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<p><a rel="nofollow" href="https://cran.r-project.org/package=survsup" target="_blank">survsup</a> v0.0.1: Implements functions to plot survival curves. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/survsup/vignettes/survsup_intro.html" target="_blank">vignette</a> provides examples.</p>
<p><img src="https://i2.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/survsup.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tidybayes" target="_blank">tidybayes</a> v1.0.1: Provides functions for composing data and extracting, manipulating, and visualizing posterior draws from Bayesian models (<code>JAGS</code>, <code>Stan</code>, <code>rstanarm</code>, <code>brms</code>, <code>MCMCglmm</code>, <code>coda</code>, …) in a tidy data format. There is a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/tidybayes/vignettes/tidybayes.html" target="_blank">Using tidy data with Bayesian Models</a>, and vignettes for <a rel="nofollow" href="https://cran.r-project.org/web/packages/tidybayes/vignettes/tidy-brms.html" target="_blank">brms</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/tidybayes/vignettes/tidy-rstanarm.html" target="_blank">rstanarm</a> models.</p>
<p><img src="https://i1.wp.com/rviews.rstudio.com/post/2018-09-21-Aug-Top40_files/tidybayes.png?w=450&ssl=1" data-recalc-dims="1" height="400"></p>
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