information:classification
Marginal densities

For i = 1, 2,..., n, let f (x) be the probability density function associated with variable X alone. This is called the marginal density function, and can be deduced from the probability density associated with the random variables X,..., X by integrating over all values of the other n − 1 variables: f X i (x i) = ∫ f (x 1, …, x n) d x 1 ⋯ d x i − 1 d x i + 1 ⋯ d x n. {\displaystyle f_{X_{i}}(x_{i})=\int f(x_{1},\ldots,x_{n})\,dx_{1}\cdots dx_{i-1}\,dx_{i+1}\cdots dx_{n}.}