R Packages You Should Put Under Your Pillow

R在统计分析、机器学习、以及绘图上有着丰富的功能,基础安装包里的函数能够满足基本的需求,如果需要更多样化、复杂的数据处理,可以试着使用以下工具:

数据清洗转换 (Data wangling)

  • DescTools (Tools for describing data and descriptive statistics)
  • dplyr (面向data.frame,plyr的下次迭代,让R具有流式数据处理的风格)
  • plyr (有用的ddply函数,参考http://www.r-bloggers.com/a-fast-intro-to-plyr-for-r/)
  • reshape (数据变形的基本操作,丰富但底层)
  • reshape2 (功能强大的melt和cast数据融合函数,reshape简版)
  • tidyr (功能简单实用的长宽数据变化,reshape2简版)

绘图及颜色 (Colors and plots)

  • colorRamps (多种颜色梯度生成,如matlab风格的颜色)
  • Colors in ggplot2 (http://bit.do/SDnT)
  • colorspace (Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL.)
  • dichromat (Focused on palettes for color-impaired viewers. Collapse red-green or green-blue distinctions to simulate the effects of different types of color-blindness.)
  • ggplot2 (小清新绘图,事实上比基础绘图函数强大很多)
  • ggvis (交互式数据可视化)
  • gplots (一些加强版数据可视化函数,如boxplot2)
  • grDevices (The base colors in core R, including well-known functions like colors, palette.)
  • gridExtra (帮助ggplot2实现窗格布局,类似于基础包里的layout,mfrow函数)
  • IDPmisc (Contains different high-level graphics functions for displaying large datasets)
  • plotrix (多种不常见但可能有用的图形)
  • RColorBrewer (The packages provides palettes for drawing nice maps shaded according to a variable)
  • rgl (支持3D图形、视频生成,包括多种格式)
  • scatterplot3d (绘制3D的散点图或平面)

模型和机器学习 (Machine learning)

  • caret (The “go to” package for machine learning, classification and regression training)
  • depmixS4 (Hidden Markov Model及其他dependent mixture model实现)
  • e1071 (Good svm implementation and other machine learning algorithms)
  • entropy (多种计算序列熵的方法)
  • partykit (Tools for plotting decision trees)
  • pracma (Functions for numerical analysis, linear algebra, optimization, differential equations and some special functions)
  • psych (源自心理学研究人员,table和相关分析等)
  • survMisc (Relatively new package with various functions for survival data extending the methods available in the survival package.)

随机分布参数估计 (Parameters estimation)

  • fBasics (包含skewness和kurtosis函数)
  • fitdistrplus (对MASS包参数估计函数的加强,同时有灵活的QQ图以及分布对比图)
  • fitting{brainwaver}
  • Goodness-of-test: goodfit{vcd}, chisq.test, ks.test, qqnorm
  • MASS (最大似然估计fitdistr函数)
  • mixdist (混合模型的参数估计)
  • mixtools (混合模型的参数估计,CRAN Cluster View更多关于mixture model 的信息)
  • Normality test: shapiro.test, jarque.bera.test{tseries}, sf.test{nortest}, ad.test{nortest}, cvm.test{nortest}, lillie.test{nortest}, pearson.test{nortest}
  • poweRlaw (重尾分布参数估计)
  • 参数估计函数:optim{stats}, mle{stats4}, fitdistr{MASS}

Misc工具箱 (Misc tookit)

  • classInt (包含离散化函数,如绘图中颜色的分阶)
  • devtools (R包开发工具箱)
  • Hmisc (functions for data analysis, graphics, utilities and much more)
  • magicaxis (magplot, magaxis, maglab etc.)
  • MASS (各种工具函数)
  • misc3d (Misc 3d plots including isosurfaces)
  • miscet (Miscellaneous R tools to simplify the working with data types and formats including functions for working with data frames and character strings)
  • miscFuncs (Some functions for Kalman filters)
  • pryr (深入理解R以及R包开发中的有用工具)
  • scales (Scales map data to aesthetics.)
  • sfsmisc (eaxis的对数坐标轴可实现类似magicaxis的效果)
  • squash (Color-based visualization of multivariate data. Map numeric values to colors)
  • stringr (Convenience wrappers for functions for manipulating strings)

优化工具 (Speedup)

  • parallel (提供mclapply对lapply()和mapply()实现并行化处理。)
  • doParallel (The “parallel backend” for foreach package. Must be enabled to use %dopar%.)
  • foreach (Using foreach without side effects also facilitates executing the loop in parallel.)
  • iterators (Support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.)

地图工具 (Map tools)

  • deldir (Calculates the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set.)
  • geosphere (functions to calculate great circle distance.)
  • GISTools (Some mapping and spatial data manipulation tools)
  • mapmisc (New package with utilities for producing maps)
  • mapproj (Mapping between lon/lat coordinates and projected surface.)
  • maps (Display of maps. Projection code and larger maps are in separate packages (mapproj and mapdata)).
  • maptools (Set of tools for manipulating and reading geographic data)
  • NCmisc (A grab bag of utilities including progress bars and function timers)
  • OpenStreetMap (Interfaces to OSM.)
  • osmar (Interfaces to OSM.)
  • splancs (Spatial Point-Pattern Analysis code in Splus.)

时空数据分析包 (Spatiotemporal)

  • CompRandFld - Collect a set of procedures for the analysis of Random Fields by Composite Likelihood methods.
  • fields (Fields is for curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics.)
  • geoR (Geostatistical analysis including traditional, likelihood-based and Bayesian methods.Geostatistical analysis including traditional, likelihood-based and Bayesian methods.)
  • gstat (Variogram modelling; simple, ordinary and universal point or block (co)kriging, sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions.)
  • PBSmapping (Facilitate the compilation and analysis of fishery data, particularly data referenced by spatial coordinates.)
  • RandomFields (Simulation of Gaussian and extreme value random fields; conditional simulation; kriging; maximum likelihood estimation.)
  • raster (Reading, writing, manipulating, analyzing and modeling of gridded spatial data.)
  • rgdal (Provides bindings to GDAL)
  • sp (Basic spatial and temporal classes and useful functions like spplot, Trellis plot, spDists, spsample.)
  • spacetime (Classes and methods for spatio-temporal data, including space-time regular lattices, sparse lattices, irregular data, and trajectories)
  • spdep (Spatial Dependence: Weighting Schemes, Statistics and Models)
  • xts (Uniform handling of R’s different time-based data classes by extending zoo)
  • zoo (For Regular and Irregular Time Serie)

空间相关性 (Spatial correlation)

  • ade4 - This package has function gearymoran that calculates Moran’s I and Geary’s c. Does not plot correlograms.
  • ape - Moran’s I test (function Moran.I) for spatial and phylogenetic autocorrelation (based on normal approximation, not on randomizations = fast). Does not plot correlograms.
  • geosphere - a bunch of spherical trigonometry functions for geographic applications.
  • mpmcorrelogram - I include it as a curiosity. It calculates Multivariate Mantel Correlograms.
  • ncf - Provides functions correlog and spline.correlog. Plots correlograms. Does randomization tests.
  • pgirmess - Has function correlog that calculates the correlogram. It uses normal approximation to test significance.
  • raster - Simple function Moran. Works on rasters. You need to specify a simple neighborhood matrix. Does not plot correlograms.
  • spatial - If I understand it correctly, this package first needs you to fit a trend surface (by kriging) and you can then calculate correlogram of this fitted surface. I haven’t gone deeper into it.
  • spdep - sp.correlogram, moran, moran.plot, moran.test, moran.mc. This is the most comprehensive package, and also the most difficult to work with. Does everything, has steep learning curve.

  • 参考: http://www.r-bloggers.com/spatial-correlograms-in-r-a-mini-overview/

其他资源 (Public domains)

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