R packages

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Background on R

R is a language and environment for statistical computing and graphics. It is a GNU object which is similar to the S language and environment which was developed by the Bell laboratories by John Chamber and colleagues.

R provides a wide variety of statistical (linear and non-linear modelling, time series analysis, classification and discrimination and etc...) and graphical techniques (low level and high level), and is highly extensible.

R is an integreated suite of software facilities for data collection, data modelling, and data forecasting with the assistance of graphical display. It consists:

  1. matrix-based calculation.
  2. an effective handing and storage facilities.
  3. integrated collection of intermediate tools for data analysis.
  4. a well-developed, simple and effective programming language which includes loops, conditions, user-defined recursive functions.

My R packages

This page provides information about software on forecasting functional data. The R packages and code may be freely copied and used. No guarantee of their reliability is given. If any errors are found, please let me know.

  1. Bayesian bandwidth estimation This package contains Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error
  2. functional data sets This package contains a number of data sets for testing the performance of forecasting methods.
  3. functional time serie analysis This package contains a number of functions that can plot, model and forecast functional data, functional time series and sliced functional time series.
  4. Hierarchical time series analysis This package contains methods for analysing and forecasting hierarchical time series.
  5. Rainbow plot, functional bagplot, and functional HDR boxplot This package contains a number of functions that can plot functional data ordered by time, depth, or density, along with a number of real data sets and toy examples.

My R packages scheduled updates

  1. Add summaryfunction to the rainbow package
  2. Change the MASE function in the ftsa package

Building R packages

  1. Building R package in Windows
  2. Building R package in Mac
  3. FileZilla to distribute to cran
  4. Tools for building R packages

R packages

  1. alr3: Methods and data to accompany Applied Linear Regression 3rd edition
  2. animation: Demonstrate Animations in Statistics
  3. Acinonyx - Next-generation interactive graphics
  4. Cluster: Cluster Analysis Extended Rousseeuw et al
  5. CvM2SL2Test: Cramer-von Mises Two Sample Tests Cramer-von Mises criterion for comparing two density estimators
  6. CircStats: Circular Statistics, from "Topics in circular Statistics" (2001)
  7. Circular: Circular Statistics
  8. Date: Functions for handling dates
  9. fBasics: Rmetrics - Markets and Basic Statistics
  10. forecast: Forecast functions for time series
  11. fpp: Statistical forecasting: principles and practice
  12. glmnet: Lasso and elastic-net regularized generalized linear models
  13. kml: K-Means for Longitudinal Data
  14. LanguageR: Data sets and functions with "Analyzing Linguistic Data: A practical introduction to statistics"
  15. Lattice: Lattice Graphics
  16. lars: Least Angle Regression, Lasso and Forward Stagewise
  17. lmtest: Testing Linear Regression Models (likelihood ratio test)
  18. mFilter: The package implements several time series filters useful for smoothing and extracting trend and cyclical components of a time series
  19. missMDA: Handling missing values with/in multivariate data analysis (principal component methods)
  20. mgcv: GAMs with GCV smoothness estimation and GAMMs by REML/PQL
  21. mnormt: The multivariate normal and t distributions
  22. MortalitySmooth: Smoothing Poisson counts with P-splines
  23. nlme: linear and nonlinear mixed effects models
  24. nortest: Tests for Normality, such as shapiro.test, ks.test, tsdiag
  25. R2WinBUGS: Running WinBUGS and OpenBUGS from R/S-PLUS
  26. RExcelInstaller (Integration of R and Excel, (use R in Excel, read/write XLS files))
  27. refund: Regression for functional data
  28. rggobi: Interface between R and GGobi
  29. rgl: 3D visualization device system (OpenGL)
  30. Rpad: Workbook-style, web-based interface to R
  31. R.matlab
  32. SCA: Simple component analysis
  33. SemiPar: Semiparametic Regression
  34. simex: Simulation Extrapolation in Measurement Error Problem
  35. snow parallel computing
  36. sos: sos
  37. Stacked plotting
  38. TSA: Time Series Analysis
  39. tree: Classification and regression trees
  40. vars: VAR modeling
  41. xtable: Export tables to LaTex or HTML
  42. How to generate multiple squre Orthogonal matrices?

Classification R packages

  1. CART: tree
  2. gbm: Generalized Boosted Regression Models
  3. knn: k-nearest neighbor
  4. lda: linear discriminant analysis
  5. multinorm: multivariate logistic regression
  6. nnet: neural networks
  7. qda: quadratic discriminant analysis
  8. randomForest: Breiman and Cutler's random forests for classification and regression
  9. svm: Support vector machine

Clustering R packages

  1. cluster
  2. mclust: Model-Based Clustering / Normal Mixture Modeling
  3. Pam: prediction analysis for microarrays

Machine Learning R packages

  1. gbm: Generalized Boosted Regression Models
  2. MARS: Multivariate Adaptive Regression Splines
  3. mlbench: Machine Learning Benchmark Methods
  4. nnet: Forward Neural Networks and Multinomial Log-Linear Models
  5. Polymars: Multivariate Adaptive Polynomial Spline Regression

Functional data analysis R packages

  1. far: Modelization for functional autoregressive processes
  2. fda: Functional data analysis
  3. fpca: Restricted MLE for functional principal component analysis
  4. mar1s: Multiplicative AR(1) with seasonal processes
  5. MFDF: Modeling functional data in finance
  6. pendensity: Density estimation with a penalized mixture approach

Functional data analysis MATLAB packages

  1. fda: Functional data analysis using R and MATLAB
  2. PACE package: Principal analysis by conditional expectation

CRAN Task View

  1. Bayesian
  2. Cluster
  3. Distribution
  4. Econometrics

R books

  1. Albert, J. (2009) Bayesian computation with R, Springer.
  2. Cook, D., and Swayne, D. F. (2007) Interactive and dynamic graphics for data analysis, Springer.
  3. Cowpertwait, P.S.P. and Metcalfe, A. V. (2009) Introductory time series with R, Springer.
  4. Everitt, B. S. and Hothorn, T. (2010) A Handbook of Statistical Analyses Using R, Chapman and Hall.
  5. Murrell, P (2006) R graphics, Chapman & Hall.
  6. Husson, F. and Le, S. and Pages, J. (2010) Exploratory multivariate analysis by example using R, Chapman & Hall.
  7. Keen, K. J. (2010) Graphics for Statistics and Data Analysis with R, Chapman and Hall.
  8. Ramsay, J., Hooker, G., and Graves, S. (2009) Functional data analysis using R and MATLAB, Springer.
  9. Robert, C. and Casella, G. (2010) Introducing Monte Carlo methods with R, Springer.
  10. Wickham, H. (2009) ggplot2, Springer.
  11. Sarkar, D. (2008) Lattice, Springer.
  12. Spector, P. (2008) Data Manipulation with R, Springer.
  13. Venables, W. N. and Ripley, B. D. (2002) Modern applied statistics with S, Springer, 4th nd, New York.

Some R books on CRAN


R graphical tools

  1. Area plot
  2. Back-to-back histogram
  3. Boxplot
  4. Contour plot
  5. Density plot
  6. Histogram plot
  7. Perspective plot
  8. Scatter plot
  9. Sunflower plot
  10. 3D scatter plot
  11. 3D bar plot

Cross validated questions and answers

  1. Produce a list of variable names in a for loop, then assign values to them

Some functionality of R

  1. A (Not So) Short Introduction to S4
  2. Add noise to numbers
  3. Animation website of Yihui Xie
  4. Assign a list of strings (Produce a list of variable name in a for loop, then assign values to them)
  5. Automatically load an add-on package whenever R is started
  6. Bartlett's test that a correlation matrix is an identity matrix
  7. Calculate the area under a curve
  8. Calinski and Harabasz stopping rule
  9. character vector
  10. Check positive definite
  11. cleversearch() in svcm package performs a greedy grid search with lookup-table
  12. Cluster analysis in R
  13. Color codes
  14. Connectivity between MATLAB and R
  15. Controlling figure and table placement in Latex
  16. Copy graphics between multiple devices
  17. Creating Identity Matrices
  18. Convert list to matrix
  19. Data analysis software
  20. Detach and install package
  21. Derivative of nonparametric curve
  22. Displaying numbers not in scientific notation
  23. Finding a function in any package
  24. Finding keywords
  25. Find the mode in R
  26. Find the mode for continuous variable in R
  27. format a string
  28. index.G1 in clusterSim package calculates Calinski and Harabasz stopping rule
  29. Extracting diagonal matrix
  30. Histograms and Density Plots
  31. How to convert the lower triangle of a matrix to a symmetric matrix
  32. How to simulate a time series
  33. Integrate function in stats package
  34. Ignore error in for-loop
  35. Jonathan Baron's R help page
  36. Lattice plots
  37. Learning R from youtube
  38. list2env
  39. List of functions in a package
  40. List of loaded packages
  41. Local polynomial kernel smoother
  42. Module
  43. ksmooth function for implementing Nadaraya-Watson kernel estimator
  44. loess function for implementing local polynomial regression fitting
  45. lowess function for scatter plot smoothing
  46. optim and optimize for one-dimensional optimization and constrOptim for constrained optimization
  47. Maximum likelihood estimation
  48. Maximum Likelihood estimation of OLS method
  49. Missing value where TRUE/FALSE needed
  50. Must-have R packages for social scientists
  51. Nonparametric regression resources in R
  52. norm (one norm, the infinity norm, the Frobenius norm, or the maximum modulus)
  53. mvtsplot
  54. Open multiple R sessions
  55. Penalized regression spline
  56. Plot area under a curve
  57. Plot math
  58. proc.time Running time of R
  59. R Wiki
  60. R workshop in 2008
  61. rcmd INSTALL --build for Windows
  62. Problem with rcmd check (ec-inconsolata)
  63. Rd files with unknown encoding problem
  64. R Color Chat
  65. R is slow
  66. Remove a pattern from R remove(list=ls(pattern = "^r..$"))
  67. Removing columns from a matrix
  68. Remove Inf in data frame
  69. Run test
  70. rgl package for 3D real-time plotting
  71. Difficulty1 in installing rgl in linux
  72. Difficulty2 in installing rgl in linux
  73. frame.plot=FALSE to remove the frame in a plot
  74. S4 classes
  75. S4 class examples
  76. Sampling with replacement in R
  77. S4 classes in 15 pages, more or less
  78. Showing graphs one by one allowing full control by users
  79. Source code in C or Fortran of built in R packages
  80. Swedish mortality data
  81. Switch function in R
  82. Time and Day conversion among different time zones
  83. Trigonometric Functions
  84. unique function in R
  85. uniroot
  86. Upgrade R
  87. Version number of a package
  88. window in time series
  89. windows in graphing in R
  90. y <- c("1,200","20,000","100","12,111") as.numeric(gsub(",","", y)) to correct the quotes
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