by Joseph Rickert

One hundred and forty-five new packages were added to CRAN in February. Here are 47 interesting packages organized into five categories; Biostatistics, Data, Data Science, Statistics and Utilities.

Biostatistics

• BaTFLED3D v0.1.7: Implements a machine learning algorithm to make predictions and determine interactions in data that varies along three independent modes. It was developed to predict the growth of cell lines when treated with drugs at different doses. The vignette shows an example with simulated data.

• DClusterm v0.1: Implements methods for the model-based detection of disease clusters. Look at the JSS paper for details.

Data

• ccafs v0.1.0: Provides access to data stored in Amazon S3 collected by the research program on Climate Change, Agriculture and Food Security. There is an introduction.

• dataseries v0.1.0: Provides access to Swiss data series from dataseries.org.

• fpp2 v2.0: Provides all of the data sets used in the online book Forecasting: Principles and Practice.

• rnaturalearthdata v0.1.0: Contains the world vector map data used in Natural Earth.

Data Science

• autothresholdr v0.2.0: Is an R port of the ImageJ image processing program. The vignette shows how to use it.

• dlib v1.0: Provides an Rcpp interface to dlib, the C++ toolkit containing machine learning algorithms and computer vision tools.

• liquidSVM v1.0.1: Provides several functions to support a fast support vector machine implementation. There is a demo vignette and supplemental installation documentation.

• OOBCurve v0.1: Provides a function to calculate the out-of-bag learning curve for random forest models built with the randomForest or ranger packages.

• opusminer v0.1-0: Provides an interface to the OPUS Miner algorithm for finding the top-k, non-redundant itemsets from transaction data.

Statistics

• BayesCombo v1.0: Implements Bayesian meta-analysis methods to combine diverse evidence from multiple studies. The vignette provides a detailed example.

• BayesianTools v0.1.0: Implements various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, differential evolution MCMCs, DREAM MCMCs, and a sequential Monte Carlo particle filter, along with diagnostic and plot functions. The vignette will get you started.

• FRK v0.1.1: Implements the Fixed Rank Kriging methods presented by Cressie and Johannesson in their 2008 paper. An extended vignette explains the math and provides several examples.

• glmmTMB v0.1.1: Provides functions to fit Generalized Linear Mixed Models using the Template Model Builder (TMB) package. There are vignettes for getting started, Covariance Structures, post-hoc MCMC, simulation, and troubleshooting.

• IMIFA v1.1.0: Provides flexible Gibbs sampler functions for fitting Infinite Mixtures of Infinite Factor Analysers and related models, introduced by Murphy et al. in a 2017 paper. The vignette shows examples.

• ImputeRobust v1.1-1: Provides new imputation methods for the mice package, based on generalized additive models for location, scale, and shape (GAMLSS) as described in de Jong, van Buuren and Spiess.

• lmvar v1.0.0: Provides functions to run linear regressions in which both the expected value and variance can vary by observation. Vignettes provide an introduction and explain the details of the math.

• metaviz v0.1.0: Implements the rainforest plots proposed by Schild & Voracek as a variant of the forest plots used for meta-analysis. The vignette describes their use.

• prophet v0.1: Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. There is a Quick Start guide.

• robustarima v0.2.5: Provides functions for fitting a linear regression model with ARIMA errors, using a filtered tau-estimate.

• rpgm v0.1.3: Provides functions that use the Ziggurat Method to generate Normal random variates quickly.

• sarima v0.4-3: Provides functions for simulating and predicting with seasonal ARIMA models. The vignette presents a use case.

• sppmix v1.0.0.0: Implements classes and methods for modeling spatial point patterns using inhomogeneous Poisson point processes, where the intensity surface is assumed to be analogous to a finite additive mixture of normal components, and the number of components is a finite, fixed or random integer.

Look here for documentation.

• walkr v0.3.4: Provides functions to sample from the interaction of a hyperplane and an N Simplex. The vignette describes the math and the algorithms involved.

Utilities

• AWR v1.11.88: Installs the compiled Java modules of the Amazon Web Services SDK for R packages interacting with AWS.

• AWR.Kinesis v1.7.3: Provides functions for fetching data from Amazon Kinesis Streams using the Java-based MultiLangDaemon.

• AWR.KMS v0.1: Provides functions to encrypt plain text and ‘decrypt’ cipher text using encryption keys hosted at Amazon Web Services Key Management Service.

• drake v2.0.0: Provides a reproducible build system for R that understands the workflow dependency structure, builds out-of-date targets, skips up-to-date targets, and offers two forms of parallel computing. There is a quickstart guide.

• filesstrings v0.3.1: Provides tools for manipulating strings and files on top of stringr.

• ggraph v1.0.1: Provides functions to extend ggplot2 to graph visualizations. There are vignettes showing how to work with Edges, Layouts, and Nodes.

• odbc v1.0.1: Uses the DBI interface to implement a connection to ODBC compatible databases.

• sonify v0.1-0: Contains a function to transform univariate data, sampled at regular or irregular intervals, into a continuous sound with time-varying frequency. The function is intended as a substitute for R’s plot function to simplify data analysis for the visually impaired.

• widgetframe v0.1.0: Provides two functions for working with htmlwidgets and iframes, which may be useful when working with WordPress or R Markdown. There is a vignette.

• wrapr v0.1.1: Contains the debugging functions DebugFnW to capture function context on error for debugging, and let to convert non-standard evaluation interfaces to standard evaluation interfaces.