Basic commands in S Plus or R language
Jiquan Chen, UT, 8/28/2012
1) Database structure between SAS, Excel, R, etc. (about data, analysis, and graphics)
2) R free-ware: brief history from S programming
3) Introduction of basic comments
Introduction of basic comments
ls()
# arrows up and down to retrieve previous commends
quit()
dir()
Data()
CO2, CO2[,2],
dim(BOD) # case sensitive
exit() # of a loop
help()
# for comments
X=2
remove(x)
x<-c(2:10)
x=x*12
3:15 # as calculator
2.5*(3:15) #other operations on Page 40
runif(10) #random number generator for 10 numbers. Howa about a number between 0 and 100?
runif (1)*100
c=c(1:20)
mean(c)
max (c)
y=sqrt(c)
#other functions can be found on Page 46
seq(-10, 10, by=2.5) #create a bin
order ()
rank()
rnorm(100) # generate 100 number following normal distribution; see other distributions on Page 49
gamma (0.2)
Source(‘xxx’) # philosophical differences in programming
Sink (“xxx”)
matrix(data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL)
scan(‘test.prn’) #read data from a file
plot(CO2[,4], CO2[,5]) # graphic capability
plot(CO2[,4], CO2[,5], xlab = "", ylab="")
plot(CO2[,4], CO2[,5], xlab = "CO2 Concentration", ylab="Uptake")
plot(CO2[,4], CO2[,5], xlab = "CO2 Concentration", ylab="Uptake", type='l')
plot(CO2)
qqnorm(y, ylim, main = "Normal Q-Q Plot",xlab = "Theoretical Quantiles", ylab = "Sample Quantiles",plot.it = TRUE,
datax = FALSE, ...)
qqplot()
boxplot()
barplot()
dotchart()
pie()
contour(x,y,z,v)
interp(x,y,z)
lines()
history()
library()
methods("summary")
help(package="Matrix")
demo()
demo(glm.vr)
data()
help.search("plot")
Examples:
library("sp") # add a new package from any open source
Packages in library ‘C:/Program Files/R/R-2.14.1/library’:
base
boot
The R Base Package
Bootstrap Functions (originally by Angelo Canty
for S)
class
Functions for Classification
cluster
Cluster Analysis Extended Rousseeuw et al.
codetools
Code Analysis Tools for R
compiler
The R Compiler Package
datasets
The R Datasets Package
deldir
Delaunay Triangulation and Dirichlet (Voronoi)
Tessellation.
foreign
Read Data Stored by Minitab, S, SAS, SPSS,
Stata, Systat, dBase, ...
geoR
Analysis of geostatistical data
graphics
The R Graphics Package
grDevices
The R Graphics Devices and Support for Colours
and Fonts
grid
The Grid Graphics Package
gstat
spatial and spatio-temporal geostatistical
modelling, prediction and simulation
KernSmooth
Functions for kernel smoothing for Wand & Jones
(1995)
lattice
Lattice Graphics
MASS
Support Functions and Datasets for Venables and
Ripley's MASS
Matrix
Sparse and Dense Matrix Classes and Methods
methods
Formal Methods and Classes
mgcv
GAMs with GCV/AIC/REML smoothness estimation
and GAMMs by PQL
nlme
Linear and Nonlinear Mixed Effects Models
nnet
Feed-forward Neural Networks and Multinomial
Log-Linear Models
parallel
Support for Parallel computation in R
RandomFields
Simulation and Analysis of Random Fields
rpart
Recursive Partitioning
sp
classes and methods for spatial data
spacetime
classes and methods for spatio-temporal data
spatial
Functions for Kriging and Point Pattern
Analysis
spatialCovariance
Computation of spatial covariance matrices for
data on rectangles
spatstat
Spatial Point Pattern analysis, model-fitting,
simulation, tests
splancs
Spatial and Space-Time Point Pattern Analysis
splines
Regression Spline Functions and Classes
stats
The R Stats Package
stats4
Statistical Functions using S4 Classes
survival
Survival analysis, including penalised
likelihood.
tcltk
Tcl/Tk Interface
tools
Tools for Package Development
utils
The R Utils Package
wavelets
A package of funtions for computing wavelet
filters, wavelet transforms and multiresolution
analyses
xts
eXtensible Time Series
zoo
S3 Infrastructure for Regular and Irregular
Time Series (Z's ordered observations)