Gamma function and Gamma Probability Distribution
Gamma function and Gamma probability density both are very important concepts in mathematics and statistics. Furthermore, understanding Gamma function and Gamma probability density helps to understand chi-square distribution which plays very important role in machine learning. Especially, in Decision Tree Learning Chi-Square distribution used. In this post, I will explain from Gamma function to Gamma probability density function that will help to understand Chi-Square distribution.
Gamma function is defined as improper integral which is
Value of Γ1
Value of Γ1/2
Gamma probability density function is
Expectation of Random Variable X of Gamma Probability Distribution Function
Variance of Random Variable X of Gamma Probability Density Function
Like, Poisson Distribution Gamma probability density function’s random variable has both expectation and variance are equal.