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Exponential Distribution in R Programming – dexp(), pexp(), qexp(), and rexp() Functions

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The exponential distribution in R Language is the probability distribution of the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate. It is a particular case of the gamma distribution. In R Programming Language, there are 4 built-in functions to generate exponential distribution:

Function

Description

dexp

Probability Density Function

pexp

Cumulative Distribution Function

qexp

Quantile Function of Exponential Distribution

rexp

Generating random numbers which are Exponentially Distributed

What is Exponential Distribution?

A random variable X is said to be exponentially distributed if it has a mean equal to 1 / λ and variance is equal to 1 / λ2 then that variable is known as Exponential Distribution.

[Tex]f\left(x \right ) = \lambda\; e^{-\lambda x}[/Tex]

dexp() Function

The dexp() function returns the corresponding values of the exponential density for an input vector of quantiles.

Syntax: dexp(x_dexp, rate)

Example: 

R

# R program to illustrate
# exponential distribution
# Specify x-values
x_dexp <- seq(1, 10, by = 0.1)
      
# Apply dexp() function              
y_dexp <- dexp(x_dexp, rate = 5)   
                
# Plot dexp values
plot(y_dexp)

Output: 

Exponential Distribution in R

Exponential Distribution in R

pexp() Function

The pexp() function returns the corresponding values of the exponential cumulative distribution function for an input vector of quantiles.

Syntax: pexp(x_pexp, rate )

R

# R program to illustrate
# exponential distribution
 
# Specify x-values
x_pexp <- seq(1, 10, by = 0.2)                                    
 
# Apply pexp() function
y_pexp <- pexp(x_pexp, rate = 1)
 
# Plot values                 
plot(y_pexp)                                                   

Output : 

Cumulative Exponential Distribution Function

Cumulative Exponential Distribution Function

qexp() Function

The qexp() function gives the possibility, we can use the qexp function to return the corresponding values of the quantile function.

Syntax: qexp(x_qexp, rate)

R

# R program to illustrate
# exponential distribution
 
# Specify x-values
x_qexp <- seq(0, 1, by = 0.2)                    
  
# Apply qexp() function
y_qexp <- qexp(x_qexp, rate = 1)
  
# Plot values                  
plot(y_qexp)                                      

Output:

Quantile Function of Exponential Distribution

Quantile Function of Exponential Distribution

rexp() Function

The rexp() function is used to simulate a set of random numbers drawn from the exponential distribution.

Syntax: rexp(N, rate )

R

# R program to illustrate
# exponential distribution
 
# Set seed for reproducibility
set.seed(500)
 
# Specify size        
N <- 100
 
# Draw exp distributed values
y_rexp <- rexp(N, rate = 1)
  
# Plot exp density 
hist(y_rexp, breaks = 50, main = "")

Output:

Histogram of 100 Exponentially Distributed Numbers

Histogram of 100 Exponentially Distributed Numbers



Last Updated : 11 Mar, 2024
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