Lecture 1 Introduction to R

732A44 Programming in R

Lecture 1Introduction to R


Self-studies of the course book

2 Lectures (1 in the beginning, 1 in the end)

Labs (computer). Compulsory submission of reports-.

One written final exam (computer)

Course book: R Cookbook, by Paul Teetor◦ knowledge of R at the advanced level:

The Art of R Programming by Norman Matloff.

Lab schedule: http://www.mattiasvillani.com/teaching/programming-in-r/

Course structure

http://shop.oreilly.com/product/9780596809164.do

http://shop.oreilly.com/product/9781593273842.do

http://www.mattiasvillani.com/teaching/programming-in-r/

http://www.mattiasvillani.com/teaching/programming-in-r/


R is an open source comprehensive statistical package, more and more used around the world.

R is a real programming language (compare to SAS or Minitab)

R is not low-level language as C or Visual Basic

Can be compared to Matlab by structure, by origin – free version of S

+ Has a lot of contributed packages covering a lot of statistical methods (also recent ones!)

- Documentation is badly structured

About R


Installing the R software

R project web site: http://www.r-project.org/

Find the mirror nearest to you when downloading

http://www.r-project.org/


Start(All )ProgramRR 2.9.0


Important menu items


Notepad++: choose ”Language” ”R”

Other editors: Rstudio and Notepad++


Specific function◦ help(function)

Help browser◦ help.start()

Search for something in help◦ help.search(“expression”)

Quick reminder of function arguments:◦ args(function)

Examples of how to use function:◦ example(function)

If some method is not installed on the computer:◦ RSiteSearch(”expression")

Getting help


R is case-sensitive Separate commands by semicolon (;) Comments: #R is a very cool language!

Data assignment:

Use -> or <-a<-3;3->b;

Preliminaries


Assign a vector

Working with vectors

The function c() combines individual values (comma-spaced) to a vector

Printing the value on screen:

Either enter the variable or use the function print()

Note that the output begins with [1]. This is the row number, and in this case x is interpreted as a row vector


Listing and removing objectsListing defined objects (vectors, matrices, data frames):

Use the function ls() with no arguments

Removing objects:

Use the function rm()


Use either ‘: ‘ or seq()

Sequences


Important: In R, operations with vectors are performed element-by-element

Some operations: Element-wise: +-*/^ log exp sin cos sqrt length –number of elements sum - sum of all elements mean max min order

Logicals:TRUE or FALSE:a<-TRUE;

> >= < <= != & (and) | (or)

Operation with vectors


Use the function matrix()

a<-matrix(values,nrow=m,ncol=n)

values is a list of values enclosed in c(), i.e. a row vector or an already defined vector.

m is the number of rows and n is the number of columns of

the matrix. The number of values must be dividable by both m and n.

The values are entered column-wise.

The identifiers nrow= and ncol= can be omitted

Note the double indexing, first number for row and second number for column

Working with matrices


Positive integral indexingx[1,6] x[2:10]

Negative integral indexingx[-(1:5)] all except elements 1:5

Indexing entire row or columnx[2,] entire row 2

Finding elements satisfying specific condition:◦ x[x>mean(x)]

Indexing


Matrix operations


Matrix operators/functions:

transpose b=t(a)

b = aT

Inverse

b=solve(a)

b = a-1 (when needed)

Matrix operations


List is a collection of objects

Lists


Collecting vectors and matrices with the same number of rows in a data frameUse the function data.frame(object 1, object 2, … , object k)

Matrices need to be protected , otherwise each column of a matrix will be identified as a single object in the data frame.

Protection is made with the function I()

Data frames


Objects within a data frame can be called upon using the syntax

dataframe$object

Data frames


Vectors, lists, data frames can be entered in R:◦ edit(variable)

Example:

myframe<-data.frame();edit(myframe);

Entering or editing data


Names of objects within a data frame can be called, set or changed by handling the object

names()

Data frames


1. Save file as comma-separated file (csv)

2. Set current working directory:◦ setwd(directory)

3. Use read.csv2(filename)

Example:setwd("Z:/732A44");mydata<-read.csv2("Counties.csv");

Read from Excel file


if (expr) {…}else{…}

If you need to connect several conditions, use ’&’ , ’&&’, ’| ’ or ’||’

Conditional execution


for (name in expr1 ){…}

while (condition){…}

Loops


Function writing must always end with writing the value which should be returned!

You may also use ”return(value)” to show what value the function should return

Writing your own functions


If several arguments need to be returned, list may be used



Obligatory arguments and arguments by default Variables can be specified in any order when you call the

function



plot(x,..) plots time series

plot(x,y) scatter plot

plot(x,y) followed by points(x,y) plots several scatterplots in one coordinate system

hist(x,..) plots a hitogram

persp(x,y,z,…) creates surface plots

Graphical procedures


99% of all moderate-size codes contain mistakes in the first version Often not easy to find mistake debug

Way 1: debug a function step-by-step from the beginning: Use debug(function) Use undebug(function)

Example: Find a step when 1+2+4+8+… becomes equal to 500 (find mistake) !

Debugging

myfun<-function(x) { i<-1; r<-0; while (r!=x) { r<-r+i; i<-i*2; } return(i);}

debug(myfun);a<-myfun(500);#after some stepsundebug(myfun);


Things to do in debug mode

n or <Enter> : run next line c : continue until you exit from the loop or from the

function Any R command, for ex. find out the value of a variable where : prints stack trace Q : quit the debugger

Debugging


Way 2: insert browser() in the suspicious place in the code:

Debugging

myfun<-function(x) { i<-1; r<-0; while (r!=x) { r<-r+i; if(r>500) browser(); i<-i*2; } return(i);}


Solving a linear system of equations

Some examples

2

12

2

1

11

12

21

21

2

1

xx

xx

x

x

bxa


Some examples

nn

iiii

xx

xx

xx

nixxy

,2,1

2,22,1

1,21,1

,22,110

1

1

1

,,1;

X

Xy εβ

Regression model


Some examples

Use help(”lm”) to learn more about this function


Huge more to find out!

• Read course books

• Use PDF manuals

• Use the help function help(”function”) or ?function

• Use Google (search for “R: what you are looking for”)

Final comments

Lecture 1 Introduction to R

Documents

Transcript of Lecture 1 Introduction to R