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@R_Experts
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@iamrezaei
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#Example_3

# Create lists.

list1 <- list(1:5)

print(list1)


list2 <-list(10:14)

print(list2)


# Convert the lists to vectors.

v1 <- unlist(list1)

v2 <- unlist(list2)


print(v1)

print(v2)


# Now add the vectors

result <- v1+v2

print(result)



[[1]]

[1] 1 2 3 4 5


[[1]]

[1] 10 11 12 13 14


[1] 1 2 3 4 5

[1] 10 11 12 13 14

[1] 11 13 15 17 19


تابع
unlist
لیست را به ماهیت اولیه اش برمیگرداند

@R_Experts
#Example_3
> A = matrix( 
+ c(2, 4, 3, 1, 5, 7), # the data elements
+ nrow=2, # number of rows
+ ncol=3, # number of columns
+ byrow = TRUE) # fill matrix by rows

> A # print the matrix
[,1] [,2] [,3]
[1,] 2 4 3
[2,] 1 5 7
> A[2, 3] # element at 2nd row, 3rd column
[1] 7
> A[2, ] # the 2nd row
[1] 1 5 7
> A[ ,3] # the 3rd column
[1] 3 7
> A[ ,c(1,3)] # the 1st and 3rd columns
[,1] [,2]
[1,] 2 3
[2,] 1 7
> dimnames(A) = list(
+ c("row1", "row2"), # row names
+ c("col1", "col2", "col3")) # column names

> A # print A
col1 col2 col3
row1 2 4 3
row2 1 5 7

> A["row2", "col3"] # element at 2nd row, 3rd column
[1] 7



@R_Experts
#Example_3

> I.1d <- function(x) {

+   sin(4*x) *

+     x * ((x * ( x * (x*x-4) + 1) - 1))

+ }

> 

> adaptIntegrate(I.1d, -2, 2, tol=1e-7)

$integral

[1] 1.635644


$error

[1] 4.024021e-09


$functionEvaluations

[1] 105


$returnCode

[1] 0



> adaptIntegrate(I.2d, rep(-1, 2), rep(1, 2), maxEval=10000)

$integral

[1] -0.01797993


$error

[1] 7.845607e-07


$functionEvaluations

[1] 10013


$returnCode

[1] 0


@R_Experts
#Example_3
ی مثال خوب و سطح بندی شده:
#Step_1

# Define the cars vector with 5 values

cars <- c(1, 3, 6, 4, 9)


# Graph the cars vector with all defaults

plot(cars)




#Step_2

# Define 2 vectors

cars <- c(1, 3, 6, 4, 9)

trucks <- c(2, 5, 4, 5, 12)


# Graph cars using a y axis that ranges from 0 to 12

plot(cars, type="o", col="blue", ylim=c(0,12))


# Graph trucks with red dashed line and square points

lines(trucks, type="o", pch=22, lty=2, col="red")


# Create a title with a red, bold/italic font

title(main="Autos", col.main="red", font.main=4)



#Step_3

# Define 2 vectors

cars <- c(1, 3, 6, 4, 9)

trucks <- c(2, 5, 4, 5, 12)


# Calculate range from 0 to max value of cars and trucks

g_range <- range(0, cars, trucks)


# Graph autos using y axis that ranges from 0 to max 

# value in cars or trucks vector.  Turn off axes and 

# annotations (axis labels) so we can specify them ourself

plot(cars, type="o", col="blue", ylim=g_range, 

   axes=FALSE, ann=FALSE)


# Make x axis using Mon-Fri labels

axis(1, at=1:5, lab=c("Mon","Tue","Wed","Thu","Fri"))


# Make y axis with horizontal labels that display ticks at 

# every 4 marks. 4*0:g_range[2] is equivalent to c(0,4,8,12).

axis(2, las=1, at=4*0:g_range[2])


# Create box around plot

box()


# Graph trucks with red dashed line and square points

lines(trucks, type="o", pch=22, lty=2, col="red")


# Create a title with a red, bold/italic font

title(main="Autos", col.main="red", font.main=4)


# Label the x and y axes with dark green text

title(xlab="Days", col.lab=rgb(0,0.5,0))

title(ylab="Total", col.lab=rgb(0,0.5,0))


# Create a legend at (1, g_range[2]) that is slightly smaller 

# (cex) and uses the same line colors and points used by 

# the actual plots 

legend(1, g_range[2], c("cars","trucks"), cex=0.8, 

   col=c("blue","red"), pch=21:22, lty=1:2)
#Example_3

# dotplot for each combination of two factors

dotplot(cyl.f~mpg|gear.f,
main="Dotplot Plot by Number of Gears and Cylinders",
xlab="Miles Per Gallon")


# scatterplot matrix

``splom(mtcars[c(1,3,4,5,6)],

   main="MTCARS Data")


@R_Experts