r: statistics? programme? and who are you? -- an abc introduction to r presented by guohui ding...
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R: Statistics? Programme?and Who are You?
-- An ABC introduction to R
Presented byGuohui Ding
R&D, SIBS, CAS8 Sept, 2004For Fudan University
Main Topics Today
• What is R?
• How to administrate R?
• How does R work?
• How to apply R for statistical problem?
• How to program your R function?
• ………
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Maunga Whau Volcano
What is R?A brief history of R
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A Topographic Map of Maunga Whau
The legend of R
• R started in the early 1990’s as a project by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, intended to provide a statistical environment in their teaching lab. The lab had Macintosh computers, for which no suitable commercial environment was available.
Robert GentlemanRoss Ihaka
R’s Parents(1)• The S language
– S: an interactive environment for data analysis developed at Bell Laboratories since 1976
– Exclusively licensed by AT&T/Lucent to Insightful Corporation, Seattle WA. Product name: “S-plus”.
You can learn more from:http://cm.bell-labs.com/cm/ms/departments/sia/S/history.html
My father is S, mother is
Scheme, but why my name
is “R”?
• The Scheme languageScheme is a statically scoped and properly tail-recursive dialect of the Lisp programming language invented by Guy Lewis Steele Jr. and Gerald Jay Sussman.
Learn more: http://swiss.csail.mit.edu/projects/scheme/
• Scheme’s underlying semantics + S’syntax = R
R’s Parents(2)
“ We have named our language R –in part to acknowledge the influence of S and in part to celebrate our own efforts.”
-- R. Ihaka R. Gentleman
-- Ihaka R. & Gentleman R., 1996
R Now
• Since mid-1997 there has been a core group who can modify the R source code CVS archive.
• The R package system CRAN (the Comprehensive
R Archive Network )
http://www.r-project.org
The characters of R
• R is “GNU S” — A language and environment for data manipula-tion, calculation and graphical display. – That is R is a Free Software (or Open source software).
(Here, Free refers to freedom, not price, although R is free in that sense as well.)
• The core of R is an interpreted computer language.– A mosaic of procedure-based programming and object-oriented
programming – Good interface to procedures written in C, C++, FORTRAN and
other languages– A flexible data exchange mechanism accessing
relational databases -ODBC, PostgreSQL, MySQL and so on.
——小偷与强盗的谈判
R and Statistics
• Most packages deal with statistics and data analysis.
• Powerful statistical graphics.
• Well crosstalking with other statistical softwares.
• Most R user are statistical experts. You can learn more modern analysis method from they by email.
• You can do it when you come across a thing no body do it before.
Install and administrate R
Focus on Windows(MS)
rowcolumn
volcano
How do I get R?• The informational web site http://www.r-project.org/• CRAN - the Comprehensive R Archive Network.
– The primary site is http://cran.r-project.org/ .Mirror sites are available for many countries.– CRAN sites have binary distributions for Windows 95, 98, ME, NT4, 2000 and XP on Intel,
for the Macintosh (System 8.6 to 9.1 and MacOS X), and for several Linux distributions.
• New releases occur frequently – about every 3 months.
Be prepared to re-install frequently.
• Also you can get it from your friends, teachers, etc.
Down it!It is about 20.6M
in size.
Using Precompiled Binary Distributions
Installing R
• Double click “rw1091.exe” using your mouse. That is OK. You can install it as all other standard MS softwares.
R Console/RGui in Windows(MS)
Command box
Graphics boxMenu
Icons
Several concepts in Administrating R
• Workspace– xxx.RData
• History– xxx.Rhistory
• Package• Object• Session • Console
Run your R codes
Load/save workspace
Load/save History
Change your working directory
-- Ihaka R. & Gentleman R., 1996
Add a new package
• Commands:– library() add a package in the library– detach(package : xxx) detach a package
• All can do in the GUI (except detach())
Load a local package
Install packages frominternet or local
Update the local package from internet
Packages in R Environment
• Basic packages– "package:methods" "package:stats" "package:graphics“
"package:utils" "package:base"
• Recommanded packages– grid; lattice;e1071…
• Contributed packages (more than 366 packages nowadays)
– ……You can see what packages loaded now by the command search().
Don’t lose your way!
• Three useful system command– getwd() Get Working Directory
– setwd() Set Working Directory
– list.files() List the Files in a Directory/Folder
Show the Demonstrations of the Packages/Functions
• Commands– demo() Demonstrations of R Functionality
– example() Run an Examples Section from the Online Help
Getting Helps
• Several commands– help.start()
– help() or ?()
– help.search()
– apropos()
• Internet searching– I like it very
much. It seems
omnipotence.
Quit R
• Command– q() Terminate an R Session
How does R work?
Basic R Structure and data manipulation
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These two components explain 100 % of the point variability.
Basic R working flow(Object orientation)
package
-- R for Beginners. Emmanuel Paradis
Object orientation• Object: a collection of atomic variables and/or other
objects that belong together
• Parlance:– class: the “abstract” definition of it– object: a concrete instance– method: other word for ‘function’– slot: a component of an object
Types of Data in R• The basic data object is a vector of elements of type:
– numeric numbers - either floating point or integer– character each element is a character string– logical each element is TRUE or FALSE– list elements can be any type of object, including other lists
• Components of the S language, such as functions, are also vectors.• Any vector can include the missing data marker NA as an element.• All vectors have a length and a mode. The functions length and mode
return this information as does the str function.• A structure consists of a data object plus additional information.
Matrices (or arrays, in general) and time series are examples of structures.
Operators
Vectors, Matrices and Arrays
• Command: – array(data = NA, dim = length(data), dimnames = NULL)
– matrix(data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL)
Lists
• List vs. Vector– list: an ordered collection of data of arbitrary types. – vector: an ordered collection of data of the same type.– Typically, vector elements are accessed by their index (an integer),
list elements by their name (a character string). But both types support both access methods.
Factors
• Factors: classification variables
• If the levels of a factor are numeric (e.g. the treatments are labelled“1”, “2”, and “3”) it is important to ensure that the data are ctually
stored as a factor and not as numeric data. Always check this by using summary.
Data frames
• data frame: is supposed to represent the typical data table that researchers come up with – like a spreadsheet.
– It is a rectangular table with rows and columns; data within each column has the same type (e.g. number, text, logical), but different columns may have different types. ( A list actually)
Subsetting
Individual elements of a vector, matrix, array or data frame are accessed with “[ ]” by specifying their index, or their name
Using R on Windows(MS)
Basic statistical analysis by R
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Rural MaleRural FemaleUrban MaleUrban Female
Death Rates in Virginia
Faked 95 percent error bars
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Mean 60.35 Mean 40.4 Mean 25.88 Mean 16.93 Mean 11.05
Data Input
• From the keyboard one by one– c( ); scan( )
• From the file– read.table(); read.csv(); read.csv2();
read.dta(); read.spss(); …
• By a spreadsheet– data.entry()– edit()– fix()– ……
Data Edit
• Commands– edit()– fix()
Tips: edit() can invokean notepad in the RGui!
Data Discription
• Commands– summary()– mean()– sd()– hist()– boxplot()– ……
Probability Distribution
Three useful prefix in Probability Distribution Function
• dxxx for the density
• pxxx for the CDF
• qxxx for the quantile function
• rxxx for the simulation(random deviates)
They are different!The seed is set by the system.
You can set seed yourselfby set.seed().
Statistical Inference• Commands
– qxxx () for the quantile function– t.test()– wilcox.test(stats)– kruskal.test(stats)– var.test();
shapiro.test();qqnorm(); qqline()
--……
Analysis of variance and Regression Analysis
• Commands– anova()– lm()– ……
Experiment Design
• Commands– sample()– power.t.test()– ……
Save Object/Data
• Every R object can be stored into and restored from a file with the commands “save” and “load”.
> save(x, file=“x.Rdata”)> load(“x.Rdata”)
• Importing and exporting data with rectangular tables in the form of tab-delimited text files.
> write.table(x, file=“x.txt”, sep=“\t”)
Graphics with R
A Friendly R Environment -- Rcmdr
If you don’t like a command line environment,
package Rcmdr may be a good choice!
Cube Root Ozone (cube root ppb)
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R programming (.R)
Program your R code own
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Control Flow
• if(cond) expr
• if(cond) cons.expr else alt.expr
• for(var in seq) expr
• while(cond) expr
• repeat expr
• break
• next
Loops
• The main loop construct in R is for. The commonest use, as in C and other languages, is to count from 1 to n.– for (i in 1:n) {
## do something}
Leaving loops
• The break and next commands allow the flow of a loop to be altered–break jumps out the loop
–next jumps to the next iteration of the loop
Avoiding Iteration• The canonical bad R program looks like this
• ## multiply two vectors• for(i in 1:n) {
d[i] <- a[i] * b[i]• }• ##compute the inner product• s <- 0• for (i in 1:n){• s <- s + d[i]• }
• The right way to do this is– s<-sum(a*b)
• apply(); lapply(); sapply()
Write R function
A function definition looks like
median <- function(x, na.rm = FALSE)
{…lots of code...## a return value}
More
• Packages
• Objects and methods
• Debugging and optimisation
• Connecting to other packages
• Interface to other programme language or DataBase
R++? ++R!
Some Resources
• A Course (The ppt is showed with R Development Core Group)– http://faculty.washington.edu/tlumley/Rcourse/
• A Paper (citing R in a publication)– Ihaka R. & Gentleman R. 1996. R: a language for data analysis and graphics. Journal of
Computational and Graphical Statistics 5: 299–314.
• Two URL– http://www.r-project.org– http://www.ats.ucla.edu/stat/
• Several Books– Using R for Data Analysis and Graphics—An Introduction. J.H. Maindonald– An Introduction to R. The R Development Core Team– simpleR –Using R for Introductory Statistics. John Verzani– R for Beginners. Emmanuel Paradis– The R Reference Manual Base Package. The R Development Core Team
Acknowledge
PhD. Qi Liu Prof. Naiqing Zhao
Prof. Gang Pei Everyone Here
Prof. Yixue Li
Any Question?