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

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

Last Updated : 25 Jun, 2020

plogis() function in R Language is used to compute logistic cumulative density of the distribution. It also creates a plot of the density of the logistic cumulative distribution.

Syntax: plogis(vec) Parameters: vec: Vector of x-values for density

Example 1:

Python3 1==

# R program to calculate 
# cumulative logistic density

# Create a vector of x-values
x <- seq(-1, 1, by = 0.1)

# Calling the plogis() function
y <- plogis(x)
y

Output:

 [1] 0.2689414 0.2890505 0.3100255 0.3318122 0.3543437 0.3775407 0.4013123
 [8] 0.4255575 0.4501660 0.4750208 0.5000000 0.5249792 0.5498340 0.5744425
[15] 0.5986877 0.6224593 0.6456563 0.6681878 0.6899745 0.7109495 0.7310586

Example 2:

Python3 1==

# R program to calculate 
# cumulative logistic density

# Create a vector of x-values
x <- seq(-20, 20, by = 0.1)

# Calling the plogis() function
y <- plogis(x)

# Plot the graph
plot(y)

Output:

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

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