More January Package Picks

by Joseph Rickert

In a recent post, I highlighted several new packages that arrived on CRAN in January that provided R users with access to data. In this post, I present additional selections for interesting January packages, organized into the categories Miscellaneous, Machine Learning, Statistics and Utilities.

Miscellaneous

• rcss v1.2: Provides functions for Solving Control Problems with Linear State Dynamics.

• stormwindmodel v0.1.0: Provides functions to calculate wind speeds for hurricanes and tropical storms in the North American Atlantic basin. One vignette describes the package and another shows how to use it.

Machine Learning

• crisp v1.0.0: Implements the convex regression with interpretable partitions (CRISP) method of predicting an outcome variable on the basis of two covariates.

• BayesS5 v1.22: Implements Bayesian Variable Selection Using Shotgun Stochastic Search with Screening (S5) useful in settings where p >> n. For details, see the paper

• classifierplots v1.3.2: Provides functions to generate a grid of binary classifier and diagnostic plots with a single function call. See the README for details.
  

• eclust v0.1.0: Provides an algorithm for clustering high-dimensional data that can be affected by an environmental factor. See the paper for details.

• EnsCat v1.1: Implements various clustering methods for categorical data. See the website for examples and the paper for the details.

• MAVE v0.1.7: Implements the MAVE (Minimum Average Variance Estimation) method of dimension reduction. Look here for the math and here for examples.

• mfe v0.1.0: Provides functions to extract meta-features from datasets to support the design of recommendation systems. The vignette provides examples.

• rsparkling v0.1.0: extends sparklyr with an interface to the H2O Sparkling Water machine learning library. The README explains how to use the package.

Statistics

• confSAM v0.1: Contains a function that computes estimates and confidence bounds for the false discovery proportion in a multiple testing environment. The vignette describes the theory and provides examples.

• pdSpecEst v1.0.0: Implements a non-parametric, geometric wavelet method to estimate autocovariance matrix of a time series that preserves positive-definiteness of the estimator. This preserves the intrepretability of the estimate as a covariance matrix and helps with computational issues. The paper describes the theory and the vignette provides an example.

• tsdecomp v0.2: Implements ARIMA model-based decompositions for quarterly and monthly time series data. The vignette describes the math.

• TSeriesMMA v0.1.1: Provides a function to calculate the Hurst surface for a time series. Multiscale, multifractical analysis (MMA) is described in a paper by Gieraltowski et al.

Utilities

• awsjavasdk v0.2.0: Provides a boilerplate of classes used to access the Amazon Web Services Java Software Development Kit via package rJava. The vignette shows how to use the package.

• colr v0.1.900: Provides functions that use Perl regular expressions to select and rename columns in dataframes, lists and numeric types. The vignette contains examples.

• flifo v0.1.4: Provides functions to create and manipulate FIFO (First In First Out), LIFO (Last In First Out), and NINO (Not In or Never Out) stacks in R. See the vignette for examples.

• fst v0.7.2: Provides functions to read and write data frames at high speed, and compress data with type-optimized algorithms that allow random access of stored data frames.
  

• manipulateWidget v0.5.1: Provides helper functions to add controls like sliders, pickers, checkboxes, etc. to interactive charts created with package htmlwidgets. The animated vignette will get you started.

• msgtools v0.2.4: Provides utilities for error, warning, and other messages in R packages, including consistency checks across messages, spell-checking, and message translations for localization. See the vignette for examples.

• padr v0.2.0: Provides functions to transform datetime data into a format ready for analysis, including aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad). There is an Introduction.

• pbdPRC v0.1-1: Implements light, yet secure remote procedure calls with a unified interface via ssh (OpenSSH) or plink/plink.exe (PuTTY). The vignette provides examples.

• reprex v0.1.1: Provides a way to send code snippets with rendered output to sites like stackoverflow and github. The README shows examples.

• restfulr v0.0.8: Models a RESTful service as if it were a list.

• sys v1.1: A replacement for base system2 with consistent behavior across platforms. Supports interruption, background tasks, and full control over STDOUT / STDERR binary or text streams. README provides some details.

• textclean v0.3.0: Provides tools to clean and process text, such as replacing or removing substrings that are not optimal for analysis. The README shows how to use them.

• tidyxl v0.2.1: Imports non-tabular data from Excel into R. The vignette shows how.

• unpivotr v0.1.0: Provides tools for converting data from complex or irregular layouts into a columnar structure. There is one vignette showing how to unpivot pivot tables from a spreadsheet, and another that shows how to work with multiple, similar tables.

• WVPlots v0.2.2: Provides examples of ggplot plots that can be generated from a standard calling interface. Here is the explanation of the concept, and here are some nice examples.