A very first Rsession Ulrich Halekoh and Sren Hjsgaard Department - - PowerPoint PPT Presentation

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A very first Rsession Ulrich Halekoh and Sren Hjsgaard Department - - PowerPoint PPT Presentation

A very first Rsession Ulrich Halekoh and Sren Hjsgaard Department of Animal Health and Bioscience, Aarhus University, Denmark Department of Mathematical Sciences, Aalborg University, Denmark August 19, 2012 Printed: August


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A very first R–session

Ulrich Halekoh† and Søren Højsgaard‡

† Department of Animal Health and Bioscience, Aarhus University, Denmark ‡ Department of Mathematical Sciences, Aalborg University, Denmark

August 19, 2012

Printed: August 19, 2012 File: firstsession-slides.tex

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Contents

1 Basics of R 3 1.1 Numbers - R as a calculator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Assignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Functions in R 6 2.1 Function arguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3 Getting help 12 4 Installing and using R packages 15

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1 Basics of R

1.1 Numbers - R as a calculator

In R you can make simple calculations like

R> (10 + 2) * 5 [1] 60

  • r apply mathematical functions like the natural logarithm

R> log(100) [1] 4.60517

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1.2 Assignment

Often one wants to store the result in a variable (or, more appropriately, an object). This is done with an“assignment operator” . There are two assignment operators in R: <- and = .

R> n <- (10 + 2) * 5 [1] 60

  • r equivalently:

R> n = (10 + 2) * 5 [1] 60

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Calculations can be made on objects, e.g:

R> n^2 [1] 3600 R> log(n) [1] 4.094345 R> sin(n) [1] -0.3048106 R> n <- n + n + 10 [1] 130

Observe: If the object already exists, its previous value is overwritten. Observe: R is case–sensitive (n and N are two different objects).

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2 Functions in R

R consists essentially of a collection of functions. A function is a rule that takes some input arguments into to some output. We have already seen several functions at work: +, *, log, sin and ^. The typical call of a function is to type the functions name followed by the input arguments in parenthesis like

R> log(123) [1] 4.812184

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We have also seen exceptions to this rule, namely

R> 123 + 234 [1] 357

However there is really a function call at work here. The function is called `+` (notice the back-quotes):

R> `+`(123,234) [1] 357

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2.1 Function arguments

To see the type of arguments that go into a function we may use the args() function:

R> args(log) function (x, base = exp(1)) NULL R> args(sin) function (x) NULL R> args('+') function (e1, e2) NULL

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We see that log() actually takes two arguments: x and base. The second argument is assigned a default value.

R> exp(1) [1] 2.718282

which means that the log() function by default calculates the natural logarithm. If we want the logarithm in base 10 we do

R> log(123, base=10) [1] 2.089905

We may verify the result as

R> 10^log(123, base=10) [1] 123

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The function rnorm() generates a random sample from a normal distribution. To see the input arguments:

R> args(rnorm) function (n, mean = 0, sd = 1) NULL

The second and third arguments have been assigned default values, so these need not to be specified. The first argument has no default value, so it must be specified:

R> rnorm( n = 4) [1] -0.05841193 0.73691489 1.11769966 -0.89322232

To sample from a normal with mean 5 and standard deviation 1, we can do

R> rnorm(n = 4, mean = 5) [1] 4.615602 7.046610 6.019073 5.345521

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It is also allowed simply to write

R> rnorm(4, 5)

because R will match the given arguments with the order in which the function expects its arguments. If we want to sample with mean 0 and standard deviation 3, we can do one of the following:

R> rnorm(n = 4, sd = 3) R> rnorm(4, 0, 3)

It is generally recommended to be explicit about naming the arguments to functions, i.e. to write rnorm(n = 4,sd = 3) rather than rnorm(4, 0, 3). Readability will be greatly enhanced – especially if returning to your work after a few months!

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3 Getting help

A very important step in learning a new program is knowing where to get help. In R there are several options.

  • If you know the name of the function you want to use: Use the manual pages

to get detailed information. For example, the function rnorm generates a random sample from a normal distribution. To get help on rnorm:

R> help(rnorm)

This opens the manual page for rnorm. Note: at the bottom of the manual pages there are usually informative examples.

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  • If you do not know the name of the function you want:

To get a list of functions with“norm”in its name, use

R> apropos("norm") [1] "dlnorm" "dnorm" "norm" [4] "normalizePath" "plnorm" "pnorm" [7] "qlnorm" "qnorm" "qqnorm" [10] "qqnorm.default" "rlnorm" "rnorm"

From here might make a guess. Alternatively, try

R> help("Normal")

  • The R–help list: You may consider subscribing to the R-help mailing list, which

is very active. Please do read the posting guide before sending a question to the list. Also, please remember that nobody is paid for answering questions on the list. Finally, please observe that any question asked on the list is available

  • n the internet.
  • Search for key words or phrases in the R-help mailing list archives, or R

manuals and help pages:

R> RSiteSearch('normal distribution')

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  • It is recommended that you install Java on your computer. a With Java

installed you can use a web-browser with the R help pages:

R> help.start()

  • There are many good Wikis on the internet, for example:

R Wiki: http://wiki.r-project.org/rwiki/ Quick-R home page: http://www.statmethods.net/

aJust search the web for“java download windows”using your favorite web search engine and you

will be taken to the relevant web pages.

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4 Installing and using R packages

Much of Rs functionality is provided by the add–on packages created by a world–wide community of R-developers. These are not shipped with the R distribution but must be installed separately. To install e.g. the doBy package you can type

R> install.packages("doBy")

You will then be prompted to select a CRAN server (there are CRAN servers all

  • ver the world; pick one close to your location).

Once the package is installed on your computer it must be“loaded”into R before it can be used:

R> library(doBy)

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Notice: A package must be loaded once per session with R, because the package is unloaded when R is shut down. It is not necessary to install the package in each R session. R packages are frequently updated on CRAN. Hence it is a good idea to ensure that you have the most recent versions on your computer. This can done by:

R> update.packages()

To see what is in the doBy package do

R> help(package=doBy)