# 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 :

 `# 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)                                        `

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:

 `# 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) `

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:

 `   `  `# 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)  `

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:

 `# 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"``) `

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