One hundred forty-six new packages stuck to CRAN in August. Below, are my “Top 40” picks in eleven categories: Computational Methods, Data, Genomics, Insurance, Machine Learning, Mathematics, Medicine, Statistics, Time Series, Utilities and Visualization.
dpseg v0.1.1: Implements an algorithm for piecewise linear segmentation of ordered data by a dynamic programming algorithm. See the vignette.
qpmadr v0.1.0: Implements the method outlined in Goldfarb & Idnani (1983) for solving quadratic problems with linear inequality, equality, and box constraints.
WoodburyMatrix v0.0.1: Implements a hierarchy of classes and methods for manipulating matrices formed implicitly from the sums of the inverses of other matrices, a situation commonly encountered in spatial statistics and related fields. See the vignette for details.
neonstore v0.2.2: Provides to access to numerous National Ecological Observatory Network (NEON) data sets through its API.
pdxTrees v0.4.0: A collection of datasets from Portland Parks and Recreation which inventoried every tree in over one hundred seventy parks and along the streets in ninety-six neighborhoods. See the vignette.
hiphop v0.0.1: Implements a method to compare the genotypes of offspring with any combination of potential parents, and scores the number of mismatches of these individuals at bi-allelic genetic markers that can be used for paternity and maternity assignment. See Huisman (2017) for background, and the vignette for an introduction.
RapidoPGS v1.0.2: Provides functions to quickly compute polygenic scores from GWAS summary statistics of either case-control or quantitative traits without LD matrix computation or parameter tuning. See Reales et al. (2020) for details and the vignette for examples.
SynthETIC v0.1.0: Implements an individual claims simulator which generates synthetic data that emulates various features of non-life insurance claims. Refer to Avanzi et al. (2020) for background and see the vignette for examples.
sparklyr.flint v0.1.1: Extends
sparklyr to include Flint time series functionality. Vignettes include Importing Data and Time Series RDD.
torch v0.0.3: Provides functionality to define and train neural networks similar to
PyTorch by Paszke et al (2019) but written entirely in R. There are vignettes on Extending Autograd, Indexing tensors, Loading data, Creating tensors, and Using autograd.
gasper v1.0.1: Provides the standard operations for signal processing on graphs including graph Fourier transform, spectral graph wavelet transform, visualization tools. See De Loynes et al. (2019) for background and the package vignette.
GeodRegr v0.1.0: Provides a gradient descent algorithm to find a geodesic relationship between real-valued independent variables and a manifold-valued dependent variable (i.e. geodesic regression). Available manifolds are Euclidean space, the sphere, and Kendall’s 2-dimensional shape space. See Shin & Oh (2020), Fletcher (2013), Kim et al. (2104)] for background.
geos v0.0.1: Provides an R API to the Open Source Geometry Engine GEOS library and a vector format with which to efficiently store
GEOS geometries. See README for an example.
pcSteiner v1.0.0: Provides functions for obtaining an approximate solution to the prize winning Steiner Tree problem that seeks a subgraph connecting a given set of vertices with the most expensive nodes and least expensive edges. This implementation uses a loopy belief propagation algorithm. There is a Tutorial.
TCIU v1.1.0: Provides the core functionality to transform longitudinal data to complex-time (kime) data using analytic and numerical techniques, visualize the original time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) and model-free classification and clustering methods. See Dinov & Velev (2021) for background. There are vignettes on Laplace Transform and Kime Surface Transforms and Workflows of TCIU Analytics.
epigraphdb v0.2.1: Provides access to the EpiGraphDB platform. There is an overview, vignettes on the API, Platform Functionality, Meta Functions and three case studies on SNP protein associations, Drug Targets and Causal Evidence.
raveio v0.0.3: implements an interface to the RAVE (R analysis and visualization of human intracranial electroencephalography data) project which aims at analyzing brain recordings from patients with electrodes placed on the cortical surface or inserted into the brain. See Mafnotti et al. (2020) for background.
tboot v0.2.0: Provides functions to simulate clinical trial data with realistic correlation structures and assumed efficacy levels by using a tilted bootstrap resampling approach. There is a tutorial on The Tilted Bootstrap and another on Bayesian Marginal Reconstruction.
BayesMRA v1.0.0: Fits sparse Bayesian multi-resolution spatial models using Markov Chain Monte Carlo. See the vignette.
bsem v1.0.0: Implements functions to allow structural equation modeling for particular cases using
rstan that includes Bayesian semi-confirmatory factor analysis, confirmatory factor analysis, and structural equation models. See Mayrink (2013) for background and the vignettes: Get Started and Exploring bsem class.
cyclomort v1.0.2: Provides functions to do survival modeling with a periodic hazard function. See Gurarie et al. (2020) and the vignette for details.
ebmstate v0.1.1: Implements an empirical Bayes, multi-state Cox model for survival analysis. See Schall (1991) for details.
fairmodels v0.2.2: Provides functions to measure fairness for multiple models including measuring a model’s bias towards different races, sex, nationalities etc. There are Basic and Advanced tutorials.
MGMM v0.3.1: Implements clustering of multivariate normal random vectors with missing elements. Clustering is achieved by fitting a Gaussian Mixture Model (GMM). See McCaw et al. (2019) for details, and the vignette for examples.
rmsb v0.0.1: Is a Bayesian companion to the
rms package which provides Bayesian model fitting, post-fit estimation, and graphics, and implements Bayesian regression models whose fit objects can be processed by
rms functions. Look here for more information.
RoBMA v1.0.4: Implements a framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias) and uses Bayesian model averaging to combine them. See Maier et al. (2020) for background and the vignettes: Fitting custom meta-analytic ensembles, Reproducing BMA, and Common warnings and errors.
tTOlr v0.2: Implements likelihood ratio statistics for one and two sample t-tests. There are two vignettes: Likelihood Ratio and False Positive Risk and P-values – Uses, abuses, and alternatives.
fable.prophet v0.1.0: Enables prophet models to be used in tidyworkflows created with fabletools. See the vignette for an introduction.
garma v0.9.3: Provides methods for estimating long memory-seasonal/cyclical Gegenbauer univariate time series processes. See Dissanayake et al. (2018) for background and the vignette for the details of model fitting.
gratis v0.2.0: Generates time series based on mixture autoregressive models. See Kang et al. (2020) for background and the vignette for an introduction to the package.
rhosa v0.1.0: Implements higher-order spectra or polyspectra analysis for time series. Brillinger & Irizarry (1998) and Lii & Helland (1981) for background and the vignette for examples.
DataEditR v0.0.5: Implements an interactive editor to allow the interactive viewing, entering and editing of data in R. See the vignette for details.
equatiomatic v0.1.0: Simplifies writing
LaReX formulas by providing a function that takes a fitted model object as its input and returns the corresponding
LaTeX code for the model. There is an Introduction and a vignette on Tests and Coverage
starschemar v1.1.0: Provides functions to obtain star schema from flat tables. The vignette shows multiple examples.
glow v0.10.1: Provides a framework for creating plots with glowing points. See the vignette for examples.
graph3d v0.1.0 Implements a wrapper for the
vis-graph that enables users to create three dimensional interactive visualizations. Look here for an example.
jsTreeR v0.1.0: Provides functions to implement interactive trees for representing hierarchical data that can be included in
Shiny apps and R markdown documents. Look here for examples.
KMunicate v0.1.0: Provides functions to produce Kaplan–Meier plots in the style recommended following the KMunicate study by Morris et al. (2019). See the vignette for examples.
rAmCharts4 v0.1.0: Provides functions to create
Shiny apps and R Markdown documents, or viewed from the R console and RStudio viewer. Look here for examples.
tabularmaps v0.1.0: Provides functions for creating tabular maps, a visualization method for efficiently displaying data consisting of multiple elements by tiling them. When dealing with geospatial data, they corrects for differences in visibility between areas. Look here and at the vignette for examples.
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