Compute Cumulative Logistic Density in R Programming - plogis() Function

Compute the Negative Binomial Cumulative Density in R Programming - pnbinom() Function

Last Updated : 25 Jun, 2020

pnbinom() function in R Language is used to compute the value of negative binomial cumulative density. It also creates a density plot of the negative binomial cumulative distribution.

Syntax: pnbinom(vec, size, prob) Parameters: vec: x-values for binomial density size: Number of trials prob: Probability

Example 1:

Python3 1==

# R program to compute
# Negative Binomial cumulative Density

# Vector of x-values
x <- seq(0, 10, by = 1)

# Calling pnbinom() Function
y <- pnbinom(x, size = 10, prob = 0.5)
y

Output:

 [1] 0.0009765625 0.0058593750 0.0192871094 0.0461425781 0.0897827148
 [6] 0.1508789063 0.2272491455 0.3145294189 0.4072647095 0.5000000000
[11] 0.5880985260

Example 2:

Python3 1==

# R program to compute
# Negative Binomial Cumulative Density

# Vector of x-values
x <- seq(0, 100, by = 1)

# Calling pnbinom() Function
y <- pnbinom(x, size = 10, prob = 0.5)

# Plot a graph
plot(y)

Output:

Compute Cumulative Logistic Density in R Programming - plogis() Function

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