A Brief Introduction to R Jun Li Dept of Statistics Stanford Univ What is R A software a dialect of the S language A system for statistical analysis and graphics Works in various OS Free under GNU General Public Licence An interpreted language easy to program A Hello World script Just type print Hello World Or hw Hello World print hw How to get help To get the usage of a function Examples See Also help lm help lm lm To open HTML help help start To search a function help search lm apropos lm Basic operations of objects Creating Listing ls ls pat a ls pat a Deleting rm a Objects 1 Two intrinsic attribute mode and length Four modes numeric eg 1 1 2 2 4e25 Inf Inf NaN character eg this is R this is R hello haha n complex eg 1 2i 1 1 2 4e4i logical FALSE or TRUE Length the number of elements of the object Objects 2 vector factor a categorical variable array a k dimension matrix matrix data frame a table composed with one or several vectors and or factors all of the same length but possibly in different modes ts time series list a list can contain any type of object Reading data in a file text ASCII files Excel SAS SPSS Getting and setting working directory getwd setwd read table scan read fwf read table 1 The main way to read data in tabular form read table file header FALSE sep Examples mydata read table fish data mydata read table c data fish data TRUE mydata read table http wwwstat stanford edu hastie stats305 Data abalone 305 TRUE read table 2 read csv read csv2 read delim read delim2 scan and read fwf scan more flexible than read table can specify the mode of the variables eg mydata scan data dat what list 0 can be used to create different objects such as vectors default matrices data frames lists read fxf Read in fixed width format eg No123 341 35 No224 531 45 read fwf fish dat widths c 3 5 4 Saving data write table x file append FALSE write x file data ncolumns if is character x 1 else 5 append FALSE sep save x y xy RData load xy RData save image load RData generating data 1 x x x x x c 1 2 3 4 5 1 5 1 5 1 seq 1 5 2 rep 1 5 Random sequences rfunc n p1 p2 n the number of data generated p1 p2 parameters of the distribution rnorm rexp rgamma rpois rcauchy rbeta rt rf rchisq rbinom Generally rfunc generate random numbers dfunc the probability density pfunc the cumulative probability density can be used to find p value qfunc the value of quantile can be used to find critival values Creating objects 1 Vector vector integer 10 vector logical 10 vector numeric 10 vector character 10 Or integer 10 logical 10 numeric 10 character 10 Creating Objects 2 Factor factor 1 3 factor 1 3 levels 1 4 factor 1 2 labels c Male Female factor 1 4 exclude 3 Creating Objects 3 Matrix matrix data NA nrow 1 ncol 1 byrow FALSE dimnames NULL matrix 3 2 3 matrix 1 6 2 3 matrix 1 6 2 3 TRUE Creating Objects 4 Data Frame data frame row names NULL x 1 4 y 1 2 z c no1 no2 no3 no4 datFr data frame x y z datFr data frame N1 x N2 y N3 z Creating Objects 5 List x 1 4 y 1 2 z c no1 no2 no3 no4 xyzList list x y z xyzList list N1 x N2 y N3 z Time series expression Converting objects 1 as something as numeric as integer as logical as character as matrix as data frame Generally conversion follows intuitive rules Converting Objects 2 Converting factors into numeric values fac factor c Male Female num as numeric fac fac factor c 1 2 num as numeric fac fac factor c 1 5 num as numeric fac Converting Objects 3 How to keep the levels as they are originally specified Answer first convert it into character then into numeric fac factor c 1 5 num as numeric as character fac Operators Arithmatic Comparison Logical Identical comparison identical and all equal Eg a c 1 1 1 0 2 b c 1 0 9 a b identical a b all equal a b The indexing system Vector x 3 x 1 3 x c 1 3 x 1 x 1 3 x c 1 3 x x 5 x x 2 0 x x 1 x c FALSE TRUE Matrix x 2 3 x 2 x 3 x 1 2 x 2 3 drop FALSE Array x 3 2 4 names Vector names x c no1 no2 no3 Matrix rownames x c r1 r2 r3 colnames x c c1 c2 c3 dimnames x list c a b c c d c e f Data Frame Simple functions exp log log10 log2 sin cos tan ctan asin acos atan choose abs sqrt sum max min which max which min range mean median var cov cor round rev sort rank scale unique na omit sample Matrix computation matrix rbind cbind solve t det diag qr eigen svd Graphics R offers a remarkable variety of graphics demo graphics demo persp The result of a graphic function cannot be assigned to an object but is sent to a graphical device Two kinds of graphical functions High level plotting functions Low level plotting functions Graphical devices x11 postscript pdf png bmp jpeg dev list dev cur dev set dev off layout layout mat mat matrix 1 4 2 2 mat matrix 1 4 2 2 byrow TRUE mat matrix c 1 3 3 2 2 High level graphical functions plot x plot x y boxplot x pairs x hist x qqplot x y image x y z persp x y z some common options type specifies the type of plot p l xlim ylim specifies the lower and upper limits of the axes xlab ylab annotates the axes main the main title sub sub title written in a smaller font Low level plotting commands points x y lines x y text x y labels segments x0 y0 x1 y1 abline a b abline h y abline v x rect x1 y1 x2 y2 title str Graphical parameters Par gives us more control to the drawing opar par par plot par opar Statistical Analyses Example mydata read table c data fish txt header TRUE pairs mydata mydata lm lm weight length width data mydata or mydata lm lm mydata weight mydata length mydata width summary mydata lm or print mydata lm Formulae A formula is typically of the form y model Common models a b X X 1 X 2 X ncol X a b only the interaction a b a b a b poly a n a b n b removes the effect of b 1 a regression through the origin 1 only the intercept Using the result Example cont names mydata lm 1 coefficients residuals effects rank 5 fitted values assign …