A probability density function (PDF) describes the likelihood of different outcomes for a continuous random variable.

A random variable is one whose value is unknown or a function that assigns values to each of an experiment’s outcomes. A random variable can be discrete or continuous.

Description Probability, statistics, reliability and decision with applications in engineering. Probability of events, discrete and continuous random variables, probability density functions and ...

Ushio Sumita, Yasushi Masuda, Classes of Probability Density Functions Having Laplace Transforms with Negative Zeros and Poles, Advances in Applied Probability, Vol. 19, No. 3 (Sep., 1987), pp.

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Build foundational knowledge of data science with this introduction ...

Fundamental methods are developed for the derivation of the probability density function and moments of rational algebraic functions of independent random variables. Laplace and Mellin integral ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model.