#Example_2

# Create two lists.

list1 <- list(1,2,3)

list2 <- list("Sun","Mon","Tue")

# Merge the two lists.

merged.list <- c(list1,list2)

# Print the merged list.

print(merged.list)

[[1]]

[1] 1

[[2]]

[1] 2

[[3]]

[1] 3

[[4]]

[1] "Sun"

[[5]]

[1] "Mon"

[[6]]

[1] "Tue"

merged.list
دو لیست را کنار یکدیگر قرار میدهد و در یک لیست ذخیره میکند

#Example_2

> A <- matrix(c(2,3,-2,1,2,2),3,2)
> A

     [,1] [,2]
[1,]    2    1
[2,]    3    2
[3,]   -2    2



> is.matrix(A)

[1] TRUE

> is.vector(A)

[1] FALSE

is.matrix( ) 
is.vector( ) 

گزاره هاي منطقي هستند
كه ارزش درست يا نادرست ميگيرند.
@R_EXperts

#Example_2

> adaptIntegrate(testFn3, rep(0,3), rep(1,3), tol=1e-4)
$integral
[1] 1

$error
[1] 2.220446e-16

$functionEvaluations
[1] 33

$returnCode
[1] 0


> testFn4 <- function(x) {
+   a = 0.1
+   s = sum((x-0.5)^2)
+   (M_2_SQRTPI / (2. * a))^length(x) * exp (-s / (a * a))
+ }
> 
> adaptIntegrate(testFn4, rep(0,2), rep(1,2), tol=1e-4)
$integral
[1] 1.000003

$error
[1] 9.843987e-05

$functionEvaluations
[1] 1853

$returnCode
[1] 0



> testFn5 <- function(x) {
+   a = 0.1
+   s1 = sum((x-1/3)^2)
+   s2 = sum((x-2/3)^2)
+   0.5 * (M_2_SQRTPI / (2. * a))^length(x) * (exp(-s1 / (a * a)) + exp(-s2 / (a * a)))
+ }
> 
> adaptIntegrate(testFn5, rep(0,3), rep(1,3), tol=1e-4)
$integral
[1] 0.9999937

$error
[1] 9.980147e-05

$functionEvaluations
[1] 59631

$returnCode
[1] 0



> testFn6 <- function(x) {
+   a = (1+sqrt(10.0))/9.0
+   prod(a/(a+1)*((a+1)/(a+x))^2)
+ }
> 
> adaptIntegrate(testFn6, rep(0,4), rep(1,4), tol=1e-4)
$integral
[1] 0.9999984

$error
[1] 9.996851e-05

$functionEvaluations
[1] 18753

$returnCode
[1] 0



> testFn7 <- function(x) {
+   n <- length(x)
+   p <- 1/n
+   (1+p)^n * prod(x^p)
+ }
> adaptIntegrate(testFn7, rep(0,3), rep(1,3), tol=1e-4)
$integral
[1] 1.000012

$error
[1] 9.966567e-05

$functionEvaluations
[1] 7887

$returnCode
[1] 0

@R_Experts

#Example_2

> MC.simple.est <- function(g, a, b, n=1e4) {
+   xi <- runif(n,a,b)      # step 1
+   g.mean <- mean(g(xi))   # step 2
+   (b-a)*g.mean            # step 3
+ }
> g <- function(x) 1/log(x)
> 
> MC.simple.est(g, 2, 4)
[1] 1.922819
> integrate(g,2,4)
1.922421 with absolute error < 7.2e-14
>

#Example_2

par(bg="gold")
attach(mtcars)
plot(wt, mpg, main="Scatterplot Example",
   xlab="Car Weight ", ylab="Miles Per Gallon ", pch=20) 

نمودار پراکنش مربوط به داده های

mtcars

xlab=" " ,ylab=" "

برچسب های محورها

pch=" "

نوع شکل نقطه ها

را تعیین میکنند

@R_Experts

#Example_2

# 3d scatterplot by factor level
cloud(mpg~wt*qsec|cyl.f,
   main="3D Scatterplot by Cylinders")

@R_Experts