Compute Beta Distribution in R Programming – dbeta(), pbeta(), qbeta(), and rbeta() Functions

Beta Distribution in R Language is defined as property which represents the possible values of probability. This article is an illustration of dbeta, pbeta, qbeta, and rbeta functions of Beta Distribution.

dbeta() Function

It is defined as Beta Density function and is used to create beta density value corresponding to the vector of quantiles.

Syntax:
dbeta(vec, shape1, shape2)

Parameter:
vec: Vector to be used
shape1, shape2: beta density of input values

Returns: beta density values for a vector of quantiles



Example :

filter_none

edit
close

play_arrow

link
brightness_4
code

# R program to illustrate the use of 
# dbeta() function
  
# Creating a vector
x_beta <- seq(0, 1.5, by = 0.025 )  
  
# Apply beta function          
y_beta <- dbeta(x_beta, shape1 = 2, shape2 = 4.5)  
  
# Plot beta values
plot(y_beta)                                       

chevron_right


Output:

pbeta() Function

It is used to create cumulative distribution function of the beta distribution.

Syntax:
pbeta(vec, shape1, shape2)

Parameter:
vec: Vector to be used
shape1, shape2: beta density of input values

Example:

filter_none

edit
close

play_arrow

link
brightness_4
code

# Specify x-values for pbeta function
x_pbeta <- seq(0, 1, by = 0.025)      
  
# Apply pbeta() function
y_pbeta <- pbeta(x_pbeta, shape1 = 1, shape2 = 4)  
  
# Plot pbeta values
plot(y_pbeta)

chevron_right


Output:

qbeta() Function

It is known as beta quantile function and used t return quantile values of the function.



Syntax:
qbeta(vec, shape1, shape2)

Parameters:
vec: Vector to be used
shape1, shape2: beta density of input values

Example:

filter_none

edit
close

play_arrow

link
brightness_4
code

    
# Specify x-values for qbeta() function
x_qbeta <- seq(0, 1, by = 0.025)
  
# Apply qbeta() function
y_qbeta <- qbeta(x_qbeta, shape1 = 1, shape2 = 4)  
  
# Plot qbeta() values
plot(y_qbeta) 

chevron_right


Output:

rbeta() Function

It is defined as a random number generator that is used to set seed and specify sample size.

Syntax:
rbeta(N, shape1, shape2 )

Parameters:
vec: Vector to be used
shape1, shape2: beta density of input values

Example:

filter_none

edit
close

play_arrow

link
brightness_4
code

# Set seed for reproducibility
set.seed(13579)
  
# Specify sample size
N <- 10000  
  
# Draw N beta distributed values
y_rbeta <- rbeta(N, shape1 = 1, shape2 = 5)   
y_rbeta
  
# Plot of randomly drawn beta density
plot(density(y_rbeta), 
     main = "beta Distribution in R")

chevron_right


Output:




My Personal Notes arrow_drop_up

Recommended Posts:


Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.


Article Tags :

Be the First to upvote.


Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.