Compute the Cumulative Poisson Density in R Programming - ppois() Function

Compute Cumulative Chi Square Density in R Programming - pchisq() Function

Last Updated : 25 Jun, 2020

pchisq() function in R Language is used to compute cumulative chi square density for a vector of elements. It also creates a density plot for chi square cumulative distribution.

Syntax: pchisq(vec, df) Parameters: vec: Vector of x-values df: Degree of Freedom

Example 1:

Python3 1==

# R program to compute 
# Cumulative Chi Square Density

# Create a vector of x-values
x <- seq(0, 10, by = 1)

# Calling pchisq() Function
y <- pchisq(x, df = 5)
y

Output:

 [1] 0.00000000 0.03743423 0.15085496 0.30001416 0.45058405 0.58411981
 [7] 0.69378108 0.77935969 0.84376437 0.89093584 0.92476475

Example 2:

Python3 1==

# R program to compute 
# Cumulative Chi Square Density

# Create a vector of x-values
x <- seq(0, 10, by = 0.1)

# Calling pchisq() Function
y <- pchisq(x, df = 5)

# Plot a graph 
plot(y)

Output:

Compute the Cumulative Poisson Density in R Programming - ppois() Function

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