2017년 3 월, CRAN에 216 개의 새로운 패키지가 추가되었습니다. 다음은 바이오 사이언스, 데이터, 데이터 과학, 통계 및 유틸리티의 다섯 가지 범주로 구성된 상위 40 대 패키지 사이트입니다.

바이오 사이언스

  • BioInstaller v0.0.3 : 필요로 하는 데이터베이스 및 참조 게놈과 함께 NGS 분석 도구와 같은 방대한 생물 정보학 분석 소프트웨어 및 데이터베이스를 설치하고 다운로드 할 수있는 도구를 제공합니다.
  • DSAIDE v0.4.0 : 사용자가 감염성 질병 전파를 시뮬레이션하고 탐색 할 수있게 해주는 Shiny Apps 컬렉션을 제공합니다.
  • treespace v1.0.0 : 계통 발생 수의 분포를 탐구하기위한 도구를 제공합니다. 이 패키지에는 R에서 시작할 수있는 Shiny 인터페이스가 포함되어 있습니다.Dengue trees, Transmission trees 및landscapes of phylogenetic trees 탐색을 위한vignette  가 있습니다.
library(treespace)
data(woodmiceTrees)
wm.res <- treespace(woodmiceTrees,nf=3)
wm.groves <- findGroves(wm.res, nclust=6)
plotGrovesD3(wm.groves)
Data

Data Science

  • anomalyDetection v0.1.1: Implements procedures to aid in detecting network log anomalies. The vignette provides examples.
  • kerasR v0.4.1: Provides an interface to the Keras Deep Learning Library, which provides specifications for describing dense neural networks, convolution neural networks (CNN), and recurrent neural networks (RNN) running on top of either TensorFlow or Theano. The vignette contains examples.
  • modeval v0.1.2: Allows users to easily compare multiple classifications models built with caret functions for small data sets. The vignette provides examples.
  • supc v0.1: Implements the self-updating process clustering algorithms proposed in Shiu and Chen. The vignette contains examples.
  • tensorflow v0.7: Provides an interface to TensorFlow, an open-source software library for numerical computation using data flow graphs.

Statistics

  • frailtyEM v0.5.4: Contains functions for fitting shared frailty models with a semi-parametric baseline hazard using the Expectation-Maximization algorithm. The vignette explains the math.
  • FRK v0.1.1: Provides functions to build, fit and predict spatial random effects, fixed rank kriging models with large datasets. The vignette introduces the theory and shows some examples.
  • hmi v0.6-3: Allows users to build single-level and multilevel imputation models using functions provided, or functions from the mice and MCMCglmm packages. There is a vignette.
  • margins v0.3.0: Ports Stata’s margins command for calculating marginal (or partial) effects. There is an introduction, a vignette on the Technical Implementation Details, and a comparison with the Stata Command.
  • mlrMBO v1.0.0: Provides a toolbox for Bayesian, model-based optimization. There is an introduction and vignettes for Mixed Space Optimization, Noisy Optimization, and Parallelization.
  • MonteCarlo v1.0.0: Simplifies Monte Carlo simulation studies by providing functions that automatically set up loops to run over parameter grids, parallelize the computations, and generate output in LaTeX tables. The vignette shows how to use it.
  • RankingProject v0.1.1: Provides functions to generate plots and tables for comparing independently sampled populations. There is an introduction and a vignette that reproduces the figures from “A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals” by Wright, Klein, and Wieczorek (2017, The American Statistician, in press).
  • rjmcmc v0.2.2: Provides functions to perform reversible-jump MCMC with the restriction introduced by Barker & Link. The vignette shows how to calculate posterior probabilities from the MCMC output.

Utilities

  • canvasXpress v1.5.2: Enables creation of visualizations using CanvasXpress, a stand-alone JavaScript library for reproducible research. The vignette shows how to get started.
  • collapsibleTree v0.1.4: Provides functions to build interactive Reingold-Tilford tree diagrams created using D3.js, where every node can be expanded and collapsed by clicking on it. There are some examples on the GitHub site.
library(Polychrome)
pal2 <- alphabet.colors(26)
rancurves(pal2)

  • RApiDatetime v0.0.3: Provides a C-level API to allow packages to access C-level R date and datetime code.
  • Rcssplot v0.2.0.0: Provides tools to style plots with cascading style sheets. The vignette shows how.
  • reticulate v0.7: Implements an R interface to Python modules, classes, and functions. When calling into Python, R data types are automatically converted to their equivalent Python types. When values are returned from Python to R, they are converted back to R types. There is an overview and a vignette describing arrays in R and Python
  • shinyWidgets v0.2.0: Provides custom input widgets for Shiny apps. See the README for examples.
  • shinyjqui v0.1.0: An extension to shiny that brings interactions and animation effects from the jQuery UI library. There is an introduction and a vignette with examples.
  • valaddin v0.1.0: Provides tools to transform functions into functions with input validation checks, in a manner suitable for both programmatic and interactive use. The vignette shows how.

 

소스: March ’17 New Package Picks · R Views