April 2023: “Top 40” New CRAN Packages
This article is originally published at https://rviews.rstudio.com/
One hundred fifty-six new packages made it to CRAN in April. Here are my “Top 40” selections in twelve categories: Computational Methods, Data, Ecology, Economics, Genomics, Machine Learning, Mathematics, Medicine, Science, Statistics, Utilities, and Visualization.
clarabel v0.4.1: Implements Clarabel, a versatile interior point solver that solves linear programs, quadratic programs, second-order cone programs, and problems with exponential and power cone constraints. See the vignette.
condor v1.0.0: Provides functions to access the Condor high performance computing environment. Files are first uploaded to a submitter machine and the resulting job is then passed on to Condor. Look here for the code.
hydroMOPSO v0.1-3: Implements a state-of-the-art Multi-Objective Particle Swarm Optimiser (MOPSO), based on the algorithm developed by Lin et al. (2018) with improvements described by Marinao-Rivas & Zambrano-Bigiarini (2020) which can be used for global optimization of non-smooth and non-linear R functions and other models that need to be run from the system console, e.g. SWAT+.
rpaleoclim v1.0.0: Implements an interface to PaleoClim, a set of free, high resolution paleoclimate surfaces covering the whole globe that includes data on surface temperature, precipitation and the standard bioclimatic variables commonly used in ecological modelling. See Brown et al. (2019) for background and the vignette.
zctaCrosswalk v2.0.0: Contains the US Census Bureau’s 2020 ZCTA to County Relationship File, as well as convenience functions to translate between States, Counties and ZIP Code Tabulation Areas (ZCTAs). See the Introduction and the vignettes Workflow with tidycensus, and Developer Notes.
EWSmethods v1.1.2: Implements methods for forecasting tipping points at the community level that include rolling and expanding window approaches to assessing abundance based early warning signals, non-equilibrium resilience measures, and machine learning. See Dakos et al. (2012), Deb et al. (2022), and Drake and Griffen (2010) for background and the vignette for an introduction.
fqacalc v1.0.0: Provides functions for calculating Floristic Quality Assessment (FQA) metrics using regional FQA databases that have been approved or approved with reservations as ecological planning models by the U.S. Army Corps of Engineers (USACE). For information on FQA see Spyreas (2019). There is an Introduction.
clptheory v0.1.0: Provides functions to compute the uniform rate of profit, the vector of price of production and the vector of labor values, and also compute measures of deviation between relative prices of production and relative values. See Basu and Moraltis (2023) for background and README for an introduction.
BREADR v1.0.1: Implements a method for estimating degrees of relatedness for extreme low-coverage genotype data and includes functions to quantify and visualize the level of confidence in the estimated degrees of relatedness. See Rohrlach et al. (2023) for package details and README for examples.
crosshap v1.2.2: Implements a local haplotyping visualization toolbox to capture major patterns of co-inheritance between clusters of linked variants, while connecting findings to phenotypic and demographic traits across individuals. See Marsh et al. (2022) for a detailed example and README for an introduction.
CCMMR v0.1: Implements the convex clustering through majorization-minimization algorithm described in Touw, Groenen, and Terada (2022) to minimize the convex clustering loss function. See README for examples.
rcccd v0.3.2: Provides functions to fit class cover catch digraph classification models. Methods are explained in Priebe et al. (2001), Priebe et al. (2003), and Manukyan and Ceyhan (2016). README contains some description.
TheOpenAir v0.1.0: Implements a wrapper using the OpenAI API as a back end to integrate
ChatGPTinto diverse data-related tasks, such as data cleansing and automating analytics scripts. See README to get started.
cyclotomic v1.1.0: Implements algorithms from the GAP project to work with cyclotomic numbers: complex numbers that can be thought of as the rational numbers extended with the roots of unity. They have applications in number theory, algebraic geometry, algebraic number theory, coding theory, in the theory of graphs and combinatorics, and in the theory of modular functions and modular curves. See README for examples.
markovmix v0.1.1: Provides functions to fit a mixture of Markov chains of higher orders from multiple sequences along with various utility functions to derive transition patterns, transition probabilities per component and component priors. See README for examples.
DiDforBigData v1.0: Provides a big-data-friendly and memory-efficient difference-in-differences estimator for staggered (and non-staggered) treatment contexts. See the Get Started Guide the vignettes Background, Examples, and Theory.
predictNNB v0.1.0: Provides tools to estimate when and where a model-guided treatment strategy may outperform a treat-all or treat-none approach using Monte Carlo simulation and evaluation of the Net Monetary Benefit. See Parsons et al. (2023) for details, the Introduction, and the vignettes on creating functions, summarising results, and detailed example.
predRupdate v0.1.0: Provides functions to evaluate the predictive performance of existing clinical prediction model given a new dataset. See Su et al. (2018), Debray et al. (2014), and Martin et al. (2018) for background and the vignettes Introduction and Technical Background.
SPARRAfairness v0.0.0.1: Provides functions to analyse the behavior and performance of the Scottish Patients At Risk of admission and Re-Admission risk score which estimates yearly risk of emergency hospital admission using electronic health records for most of the Scottish population. Analysis focuses on differential performance over demographically-defined groups. See the vignette.
kronos v1.0.0: Implements a framework to analyse circadian or otherwise rhythmic data using the familiar R linear modelling syntax, while taking care of the trigonometry under the hood. Look here for examples.
mpmsim v1.0.0: Provides functions to to simulate matrix population models with particular characteristics based on aspects of life history such as mortality trajectories and fertility trajectories, and allows the exploration of sampling error due to small sample size. See the vignettes on robustness, sampling error & propagation, and PCA.
BGFD v0.1: Implements the probability density function, cumulative distribution function, quantile function, random numbers, survival function, hazard rate function, and maximum likelihood estimates for the family of Bell-G and Complementary Bell-G distributions. See Fayomi et al. (2022), Alanzi et al.(2023), and Algarni (2022) for details.
D3mirt v1.0.3: Provides functions for identifying, estimating, and plotting descriptive multidimensional item response theory models, restricted to 3D and dichotomous or polytomous data that fit the two-parameter logistic model or the graded response model. See the vignette for an extensive introduction.
funStatTest v1.0.2: Implements two sample comparison procedures based on median-based statistical tests for functional data, described in Smida et al. (2022), Chakraborty and Chaudhuri (2015), Horvath et al. (2013, and Cuevas et al. (2004). See the vignette for examples.
lessSEM v1.4.16: Provides regularized structural equation modeling (regularized SEM) with non-smooth penalty functions (e.g., lasso) building on
lavaan. There are nine vignettes including: lessSEM, The Structural Equation Model, and Mixed Penalties.
panelhetero v1.0.0: Provides tools for estimating the degree of heterogeneity across cross-sectional units in the panel data analysis using the methods developed by Okui and Yanagi (2019) and Okui and Yanagi (2020). See the vignette.
tdsa v1.0-1: Provides functions to perform time-dependent sensitivity analysis by calculating time-dependent state and parameter sensitivities for both continuous- and discrete-time deterministic models. See Ng et al. (in review) for background and the vignette to get started.
crew.cluster v0.1.0: Extends the
crew package with worker launcher plugins for traditional high-performance computing systems to enable statisticians and data scientists to asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. Look here to get started.
duke v0.0.1: Provides functions to generate visualizations with Duke’s official suite of colors in a color blind friendly way. There is an Overview and four additional vignettes including one on the theme_duke() function.
grateful v0.2.0: Facilitates the citation of R packages used in analysis projects by providing functions to scan projects for packages used and produces documents with citations in the preferred bibliography format. Functions may be used within
quarto documents. See README for examples.
hightR v0.3.0: Implements the HIGHT block cipher encryption algorithm developed to provide confidentiality in low power consumption computing environments such Radio-Frequency Identification and Ubiquitous Sensor Network. Look here for more information.
woodendesc v0.1.0: Provides functions to simplify obtaining available packages, their version codes and dependencies from any
R repository. Uses extensive caching for repeated queries. See READMEfor examples.
ggragged v0.1.0: Extends
ggplot2 facets to panel layouts arranged in a grid with ragged edges with rows and columns of potentially varying lengths. These may be useful in representing nested or partially crossed relationships between faceting variables. See README for examples.
nndiagram v1.0.0: Generates
LaTeX code for drawing well-formatted neural network diagrams with
TikZ. Users define the number of neurons on each layer, neuron connections to keep or omit, layers considered to be oversized, and neurons to draw with lighter color. See README for instructions.
PlotTools v0.2.0: Provides functions to manipulate irregular polygons and annotate plots with legends for continuous variables and color spectra using the base graphics plotting tools. See README for an example.
Please visit source website for post related comments.