One hundred sixty-one new packages made it to CRAN in July. Here are my “Top 40” picks in seven categories: Computational Methods, Data, Genomics, Machine Learning, Science, Statistics, and Utilities.
LoopDetectR v0.1.2: Provides functions to detect feedback loops (cycles, circuits) between species (nodes) in ordinary differential equation (ODE) models. See Thomas & Kaufman (2002) for background and the vignette for information on how to use the package.
chirps v0.1.2: Implements an API client for the Climate Hazards Group InfraRed Precipitation with Station CHIRPS data: 35+ years of satellite imagery, and in-situ station data used to create gridded rainfall time series for trend analysis and seasonal drought monitoring. See the vignette for an example.
covid19mobility v0.1.1: Provides COVID-19 mobility data scrapped from different sources including Google, Apple and others. There are vignettes on Animating Covid-19 Mobility Data, How mobility data has changed in cities, Work versus Home, and US mobility trends.
covidregionaldata v0.5.0: Provides access to daily COVID-19 time series data including cases, deaths, hospitalizations, and tests for several countries and subnational regions. See README to get started.
fec16 v0.1.1: Provides access to relational data from the United States 2016 federal election cycle as reported by the Federal Election Commission including information about candidates, committees, and a variety of different financial expenditures. See the vignette for details.
palmerpenguins v0.1.0: Provides size measurements, clutch observations, and blood isotope ratios for adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Look here to get started.
bioseq v0.1.1: Provides a toolbox for manipulating DNA, RNA and amino acid sequences including functions for detection, selection, replacement, transciption and translation. There is an Introduction and a vignette on Database Preparation.
singleCellHaystack v0.3.2: Implements the singleCellHaystack algorithm as described in Vandenbon & Diez (2019) for finding differentially expressed genes in single-cell transcriptome data. The vignette offers and example.
image.binarization v0.1.1: Implements algorithms to improve optical character recognition by binarizing images (turn a color or gray scale image into a black and white image). Look here for and example.
freqtables v0.1.0: Provides functions to make tables of descriptive statistics (i.e., counts, percentages, confidence intervals) for categorical variables. Designed for the Tidyverse pipeline, it also provides functions to write results into Microsoft Word ® documents. There is a vignette on the Tidyverse pipeline and another on using the
nbTransmission v1.1.1: Provides functions to estimate the relative transmission probabilities between cases in an infectious disease outbreak. See Leavitt et al. (2020) for details, and the vignette for an Introduction.
precautionary v:0.1-2: Provides functions that enhance the design and simulation of phase 1 dose-escalation trials by adding diagnostics to examine the safety characteristics of these designs in light of expected inter-individual variation in pharmacokinetics and pharmacodynamics. See Norris (2020) for background and the vignette for an Introduction.
pspline.inference v1.0.2: Provides tools for making inferences about infectious disease outcomes using generalized additive (mixed) models with penalized basis splines (P-Splines). See Weinberger et al. (2020) for background and the vignette to get started.
SITH v1.0.1: Implements a three-dimensional stochastic model of cancer growth and mutation similar to the one described in Waclaw et al. (2015) and allows for interactive 3D visualizations of the simulated tumor. See the vignette for an Introduction.
cmstatr v0.7.0: Implements the statistical methods commonly used for advanced composite materials in aerospace applications focusing on calculating basis values (lower tolerance bounds) for material strength properties, as well as performing the associated diagnostic tests. See Kloppenborg (2020) for details and the vignettes for a Tutorial, examples of Plotting Composite Material Data and the Anderson-Darling Test.
hadron v3.1.0: Provides a tool kit to perform statistical analyses of correlation functions generated from Lattice Monte Carlo simulations including functions to extract hadronic quantities from Lattice Quantum Chromodynamics simulations (Boucaud et al. (2008)), to determine energy eigenvalues of hadronic states (Blossier et al. (2009), and Fischer et al. (2020)). There are vignettes on the Two Amplitudes Model, GEVP energy level extraction, The Hankel Method, Jackknife Covariance and Missing Values, and Jackknife Error Normalization.
sarp.snowprofile v1.0.0: Provides analysis and plotting tools for snow profile data produced from manual snowpack observations and physical snowpack models. The functions read multiple data formats, manipulate data, and produce stratigraphy and time series profiles. See the vignette for more information.
fddm v0.1-1: Implements the Diffusion Decision Model of Ratcliff & McKoon (2008) with across tial variable drift rate. It includes
C++ implementations of the approximations of Navarro & Fuss (2009) and Gondan et al. (2014). There are vignettes on Benchmark Testing, Model Fitting, Mathematical Methods, and Validation.
GGMncv v1.1.0: Provides functions to estimate Gaussian graphical models with non-convex penalties, including atan, seamless L0, exponential, smooth integration of counting and absolute deviation, logarithm, Lq, smoothly clipped absolute deviation, minimax concave penalty, Lasso, and Adaptive lasso. See README for examples.
LTRCforests v0.5.0: Implements the conditional inference forest and random survival forest algorithm to modeling left-truncated right-censored data with time-invariant covariates, and (left-truncated) right-censored survival data with time-varying covariates. See Yao et al. (2020).
MoMPCA v1.0.0: Implements a method to cluster any count data matrix with a fixed number of variables, such as document/term matrices. Inference is done by means of a greedy Classification Variational Expectation Maximisation (C-VEM) algorithm. See Jouvin et. al. (2020) for more details and the vignette for an example..
ztpln v0.1.0: Provides functions for obtaining the density, random variates, and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and its mixture distributions. See the vignette for details.
cpp11 v0.2.1: Provides a header only,
C++ 11 interface to R’s C interface and strives to be safe against long jumps from the C API and C++ exceptions, and to conform to normal R function semantics and support interactions with
ALTREP vectors. There are vignettes on Motivations, Getting Started, cpp11 Internals, and Converting from Rcpp.
rbibutils v1.0.3: Provides functions to convert between a number of bibliography formats, including
Bibentry, and includes a port of the bibutils utilities by Chris Putnam. Look here for examples.