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.

SIAM Journal on Applied Mathematics, Vol. 18, No. 4 (Jun., 1970), pp. 721-737 (17 pages) The probability density functions of products of independent beta, gamma and central Gaussian random variables ...

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 ...

Kernel Density Estimation (KDE): A nonparametric method to estimate the probability density function of a random variable by averaging over locally weighted contributions of each data point.