Logistic Function in R
Logistic Function in R, Here is a rewritten version of the article with the codes included:
Logistic Functions in R: A Tutorial
In this tutorial, we will explore the logistic functions in R, including the density, cumulative distribution function, quantile function, and random number generation.
We will use the dlogis
, plogis
, qlogis
, and rlogis
functions to demonstrate each of these functions.
Example 1: Logistic Density in R (dlogis Function)
To begin, we need to create a sequence of quantiles:
x_dlogis <- seq(-10, 10, by = 0.1)
Then, we can apply the dlogis
function:
y_dlogis <- dlogis(x_dlogis)
To visualize the output, we can plot the values:
plot(y_dlogis)
This will produce a plot of the logistic probability density function (PDF).
Example 2: Logistic Cumulative Distribution Function (plogis Function)
For the cumulative distribution function (CDF), we need to create a sequence of quantiles:
x_plogis <- seq(-10, 10, by = 0.1)
Then, we can apply the plogis
function:
y_plogis <- plogis(x_plogis)
To visualize the output, we can plot the values:
plot(y_plogis)
This will produce a plot of the logistic cumulative distribution function (CDF).
Example 3: Logistic Quantile Function (qlogis Function)
For the quantile function, we need to create a sequence of probabilities:
x_qlogis <- seq(0, 1, by = 0.01)
Then, we can apply the qlogis
function:
y_qlogis <- qlogis(x_qlogis)
To visualize the output, we can plot the values:
plot(y_qlogis)
This will produce a plot of the logistic quantile function.
Example 4: Generating Random Numbers (rlogis Function)
To generate random numbers with a logistic distribution, we need to set a seed for reproducibility and a sample size:
set.seed(123)
N <- 10000
Then, we can apply the rlogis
function:
y_rlogis <- rlogis(N)
We can print the values to the RStudio console:
y_rlogis
And create a histogram of the output:
hist(y_rlogis, breaks = 70, main = "")
This will produce a plot of the logistic density.