#R_Experts

vector1 <- c(5,9,3)
vector2 <- c(10,11,12,13,14,15)
column.names <- c("COL1","COL2","COL3")
row.names <- c("ROW1","ROW2","ROW3")
matrix.names <- c("Matrix1","Matrix2")

#R_Experts:#Take these vectors as input to the array.
result <- array(c(vector1,vector2),dim = c(3,3,2),dimnames = list(row.names,column.names,
   matrix.names))
print(result)

#R_Experts

data()

 Sys.Date() 

Sys.time()

return()

return(list())

x<-rnorm(1000)

x

y<-matrix(x,10,100)

y

vv<-rep(NA,100)

vv

for(i in 1:100){

vv[i]<-var(y[ ,i])

i=i+1

}

vv

yy<-matrix(vv,100,1)

yy

s=0

for(i in 1:100){

for(k in i:100){

if (yy[i,1] > yy[k,1]){

s=s+1}

else{s=s

}

k=k+1

}

i=i+1

}

s

> set.seed(123)

> rnorm(4)

[1] -0.56047565 -0.23017749  1.55870831  0.07050839

> rnorm(4)

[1]  0.1292877  1.7150650  0.4609162 -1.2650612

> set.seed(123)

> rnorm(4)

[1] -0.56047565 -0.23017749  1.55870831  0.07050839

> sample(1:6, 10, replace=TRUE)

 [1] 2 2 5 3 5 3 5 6 3 5

> set.seed(1)

> sample(1:6, 10, replace=TRUE)

 [1] 2 3 4 6 2 6 6 4 4 1

> sample(1:6, 10, replace=TRUE)

 [1] 2 2 5 3 5 3 5 6 3 5

> set.seed(1)

> sample(1:6, 10, replace=TRUE)

 [1] 2 3 4 6 2 6 6 4 4 1

> set.seed(123)

> index <- sample(1:nrow(iris), 5)

> index

[1] 44 119 62 133 142

> iris[index, ]

  Sepal.Length Sepal.Width Petal.Length Petal.Width  Species

44      5.0     3.5     1.6     0.6   setosa

119     7.7     2.6     6.9     2.3 virginica

62      5.9     3.0     4.2     1.5 versicolor

133     6.4     2.8     5.6     2.2 virginica

142     6.9     3.1     5.1     2.3 virginica

R> sample(LETTERS, 5)
[1] "K" "N" "R" "Z" "G"
R> sample(LETTERS, 5)
[1] "L" "P" "J" "E" "D"
R> set.seed(42); sample(LETTERS, 5)
[1] "X" "Z" "G" "T" "O"
R> set.seed(42); sample(LETTERS, 5)
[1] "X" "Z" "G" "T" "O"

mytrans <- function(x) {
  if (!is.matrix(x)) {
    warning("argument is not a matrix: returning NA")
    return(NA_real_)
  }
  y <- matrix(1, nrow=ncol(x), ncol=nrow(x))
  for (i in 1:nrow(x)) {
    for (j in 1:ncol(x)) {
      y[j,i] <- x[i,j]
    }
  }
return(y)
}

# try it
z <- matrix(1:10, nrow=5, ncol=2)
z
tz <- mytrans(z)
tz

#install.packages("rngWELL")

#install.packages("randtoolbox")

library(rngWELL)

library(randtoolbox)

halt=halton(10,dim=1)

halt

write.csv(halt,"halt.csv")

> pmin(c(1,4,9),c(2,3,10))
[1] 1 3 9

> x=1:10
> cumsum(x)
 [1]  1  3  6 10 15 21 28 36 45 55
> 

> x=1:10
> cumprod(x)
 [1]       1       2       6      24     120     720    5040   40320  362880
[10] 3628800
>