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 : 

Output: 👁 Image

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: 

Output: 👁 Image

qbeta() Function

It is known as beta quantile function and used to 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: 

Output: 👁 Image

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: 

Output: 👁 Image