Compute the Value of Empirical Cumulative Distribution Function in R Programming - ecdf() Function

Compute the value of F Cumulative Distribution Function in R Programming - pf() Function

Last Updated : 25 Jun, 2020

pf() function in R Language is used to compute the density of F Cumulative Distribution Function over a sequence of numeric values. It also plots a density graph for F Cumulative Distribution.

Syntax: pf(x, df1, df2) Parameters: x: Numeric Vector df: Degree of Freedom

Example 1:

Python3 1==

# R Program to compute 
# Cumulative F Density

# Creating a sequence of x-values
x <- seq(1, 30, by = 2)

# Calling pf() Function
y <- pf(x, df1 = 2, df2 = 3)
y

Output:

 [1] 0.5352420 0.8075499 0.8891420 0.9258675 0.9460051 0.9584308 0.9667275
 [8] 0.9725899 0.9769124 0.9802073 0.9827867 0.9848509 0.9865331 0.9879255
[15] 0.9890935

Example 2:

Python3 1==

# R Program to compute 
# Cumulative F Density

# Creating a sequence of x-values
x <- seq(1, 30, by = 0.2)

# Calling pf() Function
y <- pf(x, df1 = 3, df2 = 7)

# Plot a graph
plot(y)

Output:

Compute the Value of Empirical Cumulative Distribution Function in R Programming - ecdf() Function

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