In this lesson, you'll look at a way to represent discrete distributions - the probability mass function (PMF), which maps from each value to its probability. A probability mass function (PMF), ...

In this lesson, you'll look at a way to represent discrete distributions - the probability mass function (PMF), which maps from each value to its probability. A probability mass function (PMF), ...

Abstract: The problem of estimating a probability density function (PDF) from measurements has been widely studied by many researchers. Even though much work has been done in the area of PDF ...

The joint probability density function \(f\) of two random variables \(X\) and \(Y\) satisfies, for every \(a_1 b_1\) and \(a_2 b_2\), \[ P(a_1\le X\le b_1, a_2\le Y ...

In this paper, we propose a functional linear regression model in the space of probability density functions. We treat a cross-sectional distribution of individual earnings as an infinite dimensional ...

https://doi.org/10.2307/2581583 • https://www.jstor.org/stable/2581583 Copy URL For the statistical description of a demand process, many probability density ...

We obtain a closed form expression for the joint probability mass function of the occupation times for a Three-State Markov chain. Our representation extends the long-standing result for a Two-State ...

Advances in Applied Probability, Vol. 19, No. 3 (Sep., 1987), pp. 632-651 (20 pages) We consider a class of functions on [0,∞), denoted by Ω , having Laplace transforms with only negative zeros and ...