<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/feb-2018-top-40-new-package-picks/"></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/2018/03/29/feb-2018-top-40-new-package-picks/"> R Views</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Here are my picks for the “Top 40” packages of the 171 new packages that made it to CRAN (and stuck) in February, organized into the following categories: Computational Methods, Data, Finance, Science, Statistics, Time Series, and Utilities.</p>
<h3>Computational Methods</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=adnuts" target="_blank">adnuts</a> v1.0.0: Provides an implementation of the no-U-turn (NUTS) algorithm by <a rel="nofollow" href="http://www.jmlr.org/papers/v15/hoffman14a.html" target="_blank">Hoffman and Gelman (2014)</a> for <code>ADMB</code> and <code>TMB</code> models. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/adnuts/vignettes/adnuts.html" target="_blank">vignette</a> will get you started.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/adnuts.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=CholWishart" target="_blank">CholWishart</a> v0.9.2: Provides functions to sample from the Cholesky factorization of a Wishart random variable, the inverse Wishart distribution and the Cholesky factorization of an inverse Wishart random variable. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/CholWishart/vignettes/wishart.html" target="_blank">vignette</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=particles" target="_blank">particles</a> v0.2.1: Provides functions to simulate particle movement in 2D space using the ideas behind the ‘d3-force’ JavaScript <code>particles</code> library. It implements all forces defined in <code>d3-force</code>, as well as others such as vector fields, traps, and attractors. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/particles/vignettes/intro.html" target="_blank">vignette</a> explains how to use the package.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/particles.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=rosqp" target="_blank">rosqp</a> v0.1.0: Provides bindings to the <code>OSQP</code> solver, which can solve sparse convex quadratic programming problems with optional equality and inequality constraints.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SolveLS" target="_blank">SolveLS</a> v1.0: Implements methods including Jacobi, Gauss-Seidel, Successive Over-Relaxation, SSOR and non-stationary, Krylov subspace methods. See this <a rel="nofollow" href="https://epubs.siam.org/doi/book/10.1137/1.9780898718003" target="_blank">book</a> for details.</p>
<h3>Data</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=Cluster.OBeu" target="_blank">Cluster.OBeu</a> v1.2.1: Provides functions to estimate and return the needed parameters for visualizations designed for <a rel="nofollow" href="http://openbudgets.eu/" target="_blank">OpenBudgets</a> data. There is a vignette for <a rel="nofollow" href="https://cran.r-project.org/web/packages/Cluster.OBeu/vignettes/Cluster.OBeuOpenCPU.html" target="_blank">Using Cluster.OBeu with OpenCPU</a> and one for <a rel="nofollow" href="https://cran.r-project.org/web/packages/Cluster.OBeu/vignettes/ClusterOBeu.html" target="_blank">Cluster analysis</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=photobiologySun" target="_blank">photobiologySun</a> v0.4.0: Contains data for extraterrestrial solar spectral irradiance and ground-level solar spectral irradiance and irradiance. See <a rel="nofollow" href="doi:10.19232/uv4pb.2015.1.14" target="_blank">Aphalo P. J. (2015)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/photobiologySun/vignettes/user-guide.html" target="_blank">User Guide</a> for more information.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/photobiologySun.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SympluR" target="_blank">SympluR</a> v0.3.0: Provides functions to analyze data from the <a rel="nofollow" href="https://www.symplur.com/healthcare-social-graph/" target="_blank">Healthcare Social Graph</a> via access to the <a rel="nofollow" href="https://api.symplur.com/v1/docs" target="_blank">Symplur API</a>. Look <a rel="nofollow" href="https://www.symplur.com/healthcare-social-media-research" target="_blank">here</a> for related research articles.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/SympluR.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=totalcensus" target="_blank">totalcensus</a> v0.3.0: Allows users to download summary files from the <a rel="nofollow" href="https://www2.census.gov/" target="_blank">Census Bureau</a> and extract data – in particular, high resolution data at block, block group, and tract level – from decennial census and American Community Survey 1-year and 5-year estimates.</p>
<h3>Finance</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=estudy2" target="_blank">estudy2</a> v0.8.4: Implements event study models, including rate-of-return estimation and classical models. Tests include those proposed by [Brown and Warner (1980)](doi:10.<sup>1016</sup>⁄<sub>0304</sub>-405X(80)90002-1], [Brown and Warner (1985)](doi:10.<sup>1016</sup>⁄<sub>0304</sub>-405X(85)90042-X], [Boehmer et al. (1991)](doi:10.<sup>1016</sup>⁄<sub>0304</sub>-405X(91)90032-F>] and more. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/estudy2/vignettes/estudy2-intro.html" target="_blank">vignette</a> provides an introduction.</p>
<h3>Machine Learning</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DALEX" target="_blank">DALEX</a> v0.1.1: Provides various explainers that help to understand the link between input variables and model output in machine learning models. See this <a rel="nofollow" href="https://pbiecek.github.io/DALEX/" target="_blank">website</a> for explanations.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/DALEX.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=forestControl" target="_blank">forestControl</a> v0.1.1: Allows approximate false positive rate control in selection frequency for random forest using the methods described by <a rel="nofollow" href="arxiv:1410.2838" target="_blank">Konukoglu and Ganz (2015)</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=kmed" target="_blank">kmed</a> v0.0.1: Implements the distance-based k-medoids clustering algorithm from <a rel="nofollow" href="doi:10.1016/j.eswa.2008.01.039" target="_blank">Park and Jun (2009)</a>. Cluster validation applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/kmed/vignettes/kmedoid.html" target="_blank">vignette</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=lolR" target="_blank">lolR</a> v1.0.1: Implements optimal low-rank projection algorithms to obtain a lower-dimensional representation of data before applying supervised learning techniques in situations where the dimensionality exceeds the sample size. There are several vignettes including: <a rel="nofollow" href="https://cran.r-project.org/web/packages/lolR/vignettes/cpca.html" target="_blank">Class Condidtional PCA</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/lolR/vignettes/lrcca.html" target="_blank">Low-Rank Canonical Correlation Analysis</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/lolR/vignettes/simulations.html" target="_blank">HDLSS Simulations</a>.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/lolR.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=projpred" target="_blank">projpred</a> v0.7.0: Provides functions to perform projection predictive feature selection for generalized linear models; see, for example, <a rel="nofollow" href="doi:10.1007/s11222-016-9649-y" target="_blank">Piironen and Vehtari (2017)</a>. The package is compatible with <code>rstanarm</code>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/projpred/vignettes/quickstart.html" target="_blank">Quick Start Guide</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=RGF" target="_blank">RGF</a> v1.0.1: Implements a wrapper for the python package <a rel="nofollow" href="https://github.com/fukatani/rgf_python" target="_blank"><code>Regularized Greedy Forest</code></a>. It also includes a multi-core implementation called <a rel="nofollow" href="https://github.com/baidu/fast_rgf" target="_blank">FastRGF</a>.</p>
<h3>Science</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=cRegulome" target="_blank">cRegulome</a> v0.1.1: Provides functions to build a <code>SQLite</code> database file of pre-calculated transcription factor/microRNA-gene correlations (co-expression) incancer from the <a rel="nofollow" href="doi:10.1186/gb-2011-12-8-r83" target="_blank">Cistrome</a> and <code>miRCancerdb</code> databases. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/cRegulome/vignettes/using_cRegulome.html" target="_blank">Introduction</a> and a <a rel="nofollow" href="https://cran.r-project.org/web/packages/cRegulome/vignettes/case_study.html" target="_blank">Case Study</a>.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/cRegulome.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=CENFA" target="_blank">CENFA</a> v0.1.0: Provides tools for climate- and ecological-niche factor analysis of spatial data, including methods for visualization of spatial variability of species sensitivity, exposure, and vulnerability to climate change. See <a rel="nofollow" href="doi:10.2307/3071784" target="_blank">Hirzel et al. (2002)</a> and <a rel="nofollow" href="doi:10.1016/j.ecolmodel.2007.09.006" target="_blank">Basille et al. (2008)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/CENFA/vignettes/CENFA-vignette.html" target="_blank">vignette</a> introduces the package.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/CENFA.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=detectRUNS" target="_blank">detectRUNS</a> v0.9.5: Provides functions to detect runs of homozygosity and of heterozygosity in diploid genomes using the sliding windows ( <a rel="nofollow" href="doi:10.1086/519795" target="_blank">Purcell et al (2007)</a> ) and consecutive runs ( <a rel="nofollow" href="doi:10.1111/age.12259" target="_blank">Marras et al (2015)</a> ) methods. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/detectRUNS/vignettes/detectRUNS.vignette.html" target="_blank">vignette</a> provides an overview.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/detectRuns.png?w=456&ssl=1" data-recalc-dims="1"></p>
<h3>Statistics</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=cosa" target="_blank">cosa</a> v1.1.0: Implements generalized constrained optimal sample allocation framework for two-group multilevel regression discontinuity studies and multilevel randomized trials with continuous outcomes. There is a short <a rel="nofollow" href="https://cran.r-project.org/web/packages/cosa/vignettes/cosa_tutorial.html" target="_blank">Tutorial</a>.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/cosa.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=DirectEffects" target="_blank">DirectEffects</a> v0.1: Provides functions to estimate the controlled direct effect of treatment fixing a potential mediator to a specific value. Implements the sequential g-estimation estimator described in <a rel="nofollow" href="doi:10.1097/EDE.0b013e3181b6f4c9" target="_blank">Vansteelandt (2009)</a> and <a rel="nofollow" href="doi:10.1017/S0003055416000216" target="_blank">Acharya et al. (2016)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/DirectEffects/vignettes/DirectEffects.html" target="_blank">vignette</a> introduces the package.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/DirectEffects.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=dnr" target="_blank">dnr</a> v0.3.2: Provides functions to fit temporal lag models to dynamic networks built on top of exponential random graph models (ERGM) framework. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/dnr/vignettes/dnr_vignette.pdf" target="_blank">vignette</a> describes the method.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/dnr.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=geozoning" target="_blank">geozoning</a> v1.0.0: Provides a zoning method and a numerical criterion for assessing zoning quality. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/geozoning/vignettes/zoningObjects.pdf" target="_blank">Geozoning Structures</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/geozoning/vignettes/zoningSimu.pdf" target="_blank">Simulated Data</a>.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/geozoning.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=GpGp" target="_blank">GpGp</a> v0.1.0: Provides functions for Gaussian process predictions and conditional simulations, along with covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres. The original approximation is due to <a rel="nofollow" href="http://www.jstor.org/stable/2345768" target="_blank">Vecchia (1988)</a>, and the reordering and grouping methods are from <a rel="nofollow" href="doi:10.1080/00401706.2018.1437476" target="_blank">Guinness (2018)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/GpGp/vignettes/vignette_windspeed.html" target="_blank">vignette</a> contains an example using wind speed.</p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/GpGp.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=idealstan" target="_blank">idealstan</a> v0.2.7: Offers item-response theory (IRT) ideal-point scaling/dimension reduction methods that incorporate additional response categories and missing/censored values. Full and approximate Bayesian inference is done via the <a rel="nofollow" href="https://rviews.rstudio.com/2018/03/29/feb-2018-top-40-new-package-picks/www.mc-stan.org" target="_blank">Stan engine</a>. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/idealstan/vignettes/Package_Introduction.html" target="_blank">Introduction</a> and a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/idealstan/vignettes/How_to_Evaluate_Models.html" target="_blank">Evaluating Models</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=kdensity" target="_blank">kdensity</a> v1.0.0: Provides methods for univariate non-parametric density estimation with <a rel="nofollow" href="doi:10.1214/aos/1176324627" target="_blank">parametric starts</a> and asymmetric kernels. See <a rel="nofollow" href="doi:10.1023/A:1004165218295" target="_blank">Chen (2000)</a>, <a rel="nofollow" href="doi:10.1016/S0167-9473(99)00010-9" target="_blank">Chen (1999)</a>, and <a rel="nofollow" href="doi:10.1093/biomet/asm068" target="_blank">Jones &amp; Henderson (2007)</a>. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/kdensity/vignettes/tutorial.html" target="_blank">Tutorial</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=NetLogoR" target="_blank">NetLogoR</a> v0.3.2: Provides functions to create agent-based models in R following the <code>NetLogo</code> framework. See <a rel="nofollow" href="http://ccl.northwestern.edu/netlogo/" target="_blank">Wilensky (1999)</a>. The <code>NetLogo</code> models <a rel="nofollow" href="http://ccl.northwestern.edu/netlogo/models/Ants" target="_blank">Ants</a> and <a rel="nofollow" href="http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation" target="_blank">Wolf-Sheep-Predation</a> have been translated in R. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/NetLogoR/vignettes/ProgrammingGuide.html" target="_blank">Programming Guide</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/NetLogoR/vignettes/NLR-Dictionary.html" target="_blank">Data Dictionary</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=riskyr" target="_blank">riskyr</a> v0.1.0: Provides functions to express risk-related information in terms of probabilities or frequencies to make the teaching and training of risk literacy more transparent. There is a <a rel="nofollow" href="https://cran.r-project.org/web/packages/riskyr/vignettes/A_user_guide.html" target="_blank">User Guide</a> and <a rel="nofollow" href="https://cran.r-project.org/web/packages/riskyr/vignettes/E_riskyr_primer.html" target="_blank">Quick Start Primer</a>, along with vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/riskyr/vignettes/B_data_formats.html" target="_blank">Data Formats</a>, the <a rel="nofollow" href="https://cran.r-project.org/web/packages/riskyr/vignettes/C_confusion_matrix.html" target="_blank">Confusion Matrix and Metrics</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/riskyr/vignettes/D_functional_perspectives.html" target="_blank">Functional Perspectives</a>.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/riskyr.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=rsimsum" target="_blank">rsimsum</a> v0.3.0: Provides functions to summarize results from simulation studies and compute Monte Carlo standard errors of commonly used summary statistics. This package is modeled on the <a rel="nofollow" href="http://www.stata-journal.com/article.html?article=st0200" target="_blank"><code>simsum</code></a> user-written command in <code>Stata</code>. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/rsimsum/vignettes/introduction.html" target="_blank">Introduction</a> and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/rsimsum/vignettes/plotting.html" target="_blank">Visualization</a>,<br>
<a rel="nofollow" href="https://cran.r-project.org/web/packages/rsimsum/vignettes/relhaz.html" target="_blank">Simulating a simulation study</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/rsimsum/vignettes/rsimsumtidyverse.html" target="_blank">rsimsum and the tidyverse</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=SimCorrMix" target="_blank">SimCorrMix</a> v0.1.0: Provides functions to generate continuous (normal, non-normal, or mixture distributions), binary, ordinal, and count (regular or zero-inflated, Poisson or Negative Binomial) variables with a specified correlation matrix, or one continuous variable with a mixture distribution. This package can be used to simulate data sets that mimic real-world clinical or genetic data sets (i.e., plasmodes, as in <a rel="nofollow" href="doi:10.1016/j.csda.2008.02.032" target="_blank">Vaughan et al. (2009)</a>. There are vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimCorrMix/vignettes/cont_mixture.html" target="_blank">Continuous Mixture Distributions</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimCorrMix/vignettes/corr_mixture.html" target="_blank">Expected Cumulants and Correlations for Continuous Mixture Variables</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimCorrMix/vignettes/method_comp.html" target="_blank">Comparison of Correlation Methods</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimCorrMix/vignettes/variable_types.html" target="_blank">Variable Types</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/SimCorrMix/vignettes/workflow.html" target="_blank">Overall Workflow for Generation of Correlated Data</a></p>
<p><img alt="" src="https://i2.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/SimCorrMix.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tree.bins" target="_blank">tree.bins</a> v0.1.0: Allows users to recategorize the factors variables through a decision tree method derived from the <code>rpart()</code> function of the <code>rpart</code> package. For details, see <a rel="nofollow" href="http://www.statedu.ntu.edu.tw/bigdata/The%20Elements%20of%20Statistical%20Learning.pdf" target="_blank">Hastie et al (2009)</a> and the <a rel="nofollow" href="https://cran.r-project.org/web/packages/tree.bins/vignettes/tree.bins.html" target="_blank">vignette</a>.</p>
<h3>Time Series</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=segclust2d" target="_blank">segclust2d</a> v0.1.0: Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. The segmentation method is a bivariate extension of Lavielle’s method available in <code>adehabitatLT</code> <a rel="nofollow" href="doi:10.1016/S0304-4149(99)00023-X" target="_blank">Lavielle (1999)</a> and <a rel="nofollow" href="doi:10.1016/j.sigpro.2005.01.012" target="_blank">Lavielle (2005)</a>. The segmentation/clustering method is an extension of <a rel="nofollow" href="doi:10.1111/j.1541-0420.2006.00729.x" target="_blank">Picard et al (2007)</a>. The <a rel="nofollow" href="https://cran.r-project.org/web/packages/segclust2d/vignettes/segclust.html" target="_blank">vignette</a> contains several examples.</p>
<p><img alt="" src="https://i1.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/segclust2d.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=tstools" target="_blank">tstools</a> v0.3.6: Provides functions to plot official statistics time series with automatic legends, highlight windows, stacked bar chars with positive and negative contributions, and other options. It includes a fast, <code>data.table</code> backed time series I/O that allows the user to export / import long format, wide format, and transposed wide format data to various file types. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/tstools/vignettes/tstools.html" target="_blank">vignette</a> for details.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/tstools.png?w=456&ssl=1" data-recalc-dims="1"></p>
<h3>Utilities</h3>
<p><a rel="nofollow" href="https://cran.r-project.org/package=codemetar" target="_blank">codemetar</a> v0.1.5: Provides utilities to generate, parse, and modify <code>codemeta.json</code> files automatically for R packages, as defined in the <a rel="nofollow" href="https://codemeta.github.io/" target="_blank">Codemeta Project</a>. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/codemetar/vignettes/A-codemeta-intro.html" target="_blank">Introduction</a> to the Codemeta Project, and vignettes on <a rel="nofollow" href="https://cran.r-project.org/web/packages/codemetar/vignettes/B-translating.html" target="_blank">Translating Between Data Formats</a>, <a rel="nofollow" href="https://cran.r-project.org/web/packages/codemetar/vignettes/C-validation-in-json-ld.html" target="_blank">Validating JSON-LD</a>, and <a rel="nofollow" href="https://cran.r-project.org/web/packages/codemetar/vignettes/D-codemeta-parsing.html" target="_blank">Examples</a>.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=knitrProgressBar" target="_blank">knitrProgressBar</a> v1.1.0: Provides a progress bar similar to <code>dplyr</code> that can write progress out to a variety of locations, including <code>stdout()</code>, <code>stderr()</code>, or from <code>file()</code>. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/knitrProgressBar/vignettes/example_progress_bars.html" target="_blank">Example</a> and a <a rel="nofollow" href="https://cran.r-project.org/web/packages/knitrProgressBar/vignettes/multiprocessing.html" target="_blank">vignette</a> for setting up.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=msgpack" target="_blank">msgpack</a> v1.0: Implements a fast, C-based encoder and streaming decoder for the <code>messagepack</code> data format.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=pmatch" target="_blank">pmatch</a> v0.1.3: Implements type constructions and pattern matching. See the <a rel="nofollow" href="https://cran.r-project.org/web/packages/pmatch/README.html" target="_blank">README</a> for details.</p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=shinyalert" target="_blank">shinyalert</a> v1.0: Provides functions to create pretty popup messages (modals) in <code>Shiny</code> that may contain text, images, OK/Cancel buttons, an input to get a response from the user, and many more customizable options.</p>
<p><img alt="" src="https://i0.wp.com/rviews.rstudio.com/post/2018-03-21-Feb2018-Top40_files/shinyalert.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p><a rel="nofollow" href="https://cran.r-project.org/package=trackr" target="_blank">trackr</a> v0.7.5: Provides functions to automatically annotate R-based artifacts with relevant descriptive and provenance-related notes, and provides a back-end-agnostic storage and discoverability system for organizing, retrieving, and interrogating such artifacts. There is an <a rel="nofollow" href="https://cran.r-project.org/web/packages/trackr/vignettes/index.html" target="_blank">Introduction</a> and<br>
a vignette on <a rel="nofollow" href="https://cran.r-project.org/web/packages/trackr/vignettes/Extending-trackr.pdf" target="_blank">Extending trackr</a>.</p>
<p> </p>
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