R
Install
sudo apt-get build-dep r-base
sudo apt-get install r-base-core
install.packages('forecast',dep=TRUE,clean=TRUE)
update.packages()
R CMD INSTALL packages.tar.gz
library(forecast)
library(gsarima)
summary(x)
attributes(x)
require("forecast")
require("expsmooth")
library(forecast)
library(gsarima)
require(stats)
require(tikzDevice)
require(Rwave)
require("fUnitRoots")
sudo apt-get build-dep r-base
sudo apt-get install r-base-core
install.packages('forecast',dep=TRUE,clean=TRUE)
install.packages(c("pkg1", "pkg2"),dep=TRUE,clean=TRUE)
install.packages(c("alabama", "BB", "boot", "clue", "cmaes", "dclone", "DEoptim", "desirability", "gafit", "genalg", "glpk", "goalprog", "gsl", "igraph", "kernlab", "limSolve", "linprog", "LowRankQP", "lpSolve", "lpSolveAPI", "maxLik", "mco", "minpack.lm", "minqa", "neldermead", "nleqslv", "optimx", "optmatch", "pso", "quadprog", "quantreg", "rcdd", "Rcgmin", "Rcplex", "RcppDE", "Rcsdp", "rgenoud", "Rglpk", "Rmosek", "rneos", "ROI", "Rsolnp", "Rsymphony", "Rvmmin", "sna", "soma", "subplex", "trust", "TSP", "ucminf"),dep=TRUE,clean=TRUE)
update.packages()
R CMD INSTALL packages.tar.gz
library(forecast)
library(gsarima)
summary(x)
attributes(x)
RSiteSearch('topic')
sessionInfo()
apropos(table) #Find Objects by (Partial) Name
ls() #shows the variables in the workspace
help (name) #provides help about "name"
? name #does the same
rm(variable) #removes that variable
rm(list = ls()) #removes all variables from the work space
names(table) #what are the variables inside the table
variable <-c(value1,value2,value3 ...) #assigns values to a variable.
newvariable <- cbind (variable1, variable2, variable3 ... variable n)# make up a new array with these variables
library(gregmisc)
permutations(3, 3, letters[1:3])
library(sciplot)
lineplot.CI
lm : used to fit linear models
x1 <- runif(100)
x2 <- rexp(100)
y <- 3 + 4*x1 + 5*x2 + rnorm(100)
mod <- lm(y~x1+x2)
plot(mod)
set.seed(12345)
res1<-rbinom(10000,1,.1)
rdata3<-transform(data.frame(res1),
mdat <- matrix(c(1,2,3,11,12,13,21,22,23), nrow = 3, ncol=3, byrow=TRUE,)
mdat
matrix(data = NA, nrow = 1, ncol = 1, byrow = FALSE,dimnames = NULL)
c(list(A=c(1,2), B=c(E=7)), recursive=TRUE)
c(list(A=c(1,2), B=c(E=7,2,3,4,5)), recursive=TRUE)
c(list(A=c(1,2,A=10), B=c(E=7,2,3,4,5)), recursive=TRUE)
x<-read.table(trc)
x<-scan("trace")
write.table(b[], file = "aa.txt")
#write(wframe[i], file = "ufhfui",append = TRUE, sep = "\n")
unlink("output_file")
>sprintf( "%05f", x )
> formatC(c(1, 19), flag=0, width=3)
edit pdf
options(useFancyQuotes=FALSE)
system(noquote(paste
("pdftools -S",dQuote(paste("attachfiles=C:\\test1.pdf|C:\\Document-1.pdf")),paste("-i C:\\test2.pdf -o C:\\test3.pdf"))
))
# create a 2 by 5 matrix
x <- 1:10
attr(x,"dim") <- c(2, 5)
x<-read.table("trc")
write.table
mean(x)
> a<- matrix(c(1,3,2,4),nrow=2,ncol=2,)
> a
[,1] [,2]
[1,] 1 2
[2,] 3 4
> b<-matrix(c(0,6,5,7),nrow=2,ncol=2,)
> b
[,1] [,2]
[1,] 0 5
[2,] 6 7
> a%x%b #Kronecker product
[,1] [,2] [,3] [,4]
[1,] 0 5 0 10
[2,] 6 7 12 14
[3,] 0 15 0 20
[4,] 18 21 24 28
if( any(x <= 0) )
y <- log(1+x)
else
y <- log(x)
y <- if( any(x <= 0) ) log(1+x) else log(x)
require(stats)
centre <- function(x, type) {
switch(type,
mean = mean(x),
median = median(x),
trimmed = mean(x, trim = .1))
}
x <- rcauchy(10)
centre(x, "mean")
centre(x, "median")
centre(x, "trimmed")
ccc <- c("b","QQ","a","A","bb")
for(ch in ccc)
cat(ch,":", switch(EXPR = ch, a=1,b=2:3), "\n")
for(ch in ccc)
cat(ch,":", switch(EXPR = ch, a=, A=1, b=2:3, "Otherwise: last"),"\n")
for(i in c(-1:3,9)) print(switch(i, 1,2,3,4))
test1 <- function(x = pi, dig = 3)
{
oo <- options(digits = dig); on.exit(options(oo));
cat(.Options$digits, x, "\n")
}
test2 <- function(x = pi, dig = 3)
{
.Options$digits <- dig
cat(.Options$digits, x, "\n")
}
switch(1, invisible(pi), pi)
switch(2, invisible(pi), pi)
dump("x", file=stdout())