So far, you learned about discrete random variables and how to calculate or visualize their distribution functions. In this lesson, you'll learn about continuous variables and probability density ...

A Probability Density Function (PDF) helps identify the regions in the distribution where observations are more likely to occur, in other words, where the observation occurrence is more dense. It is ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

Abstract: Probabilistic models for the power output of Wind Electric Conversion Systems (WECS) are considered. Wind speeds are modeled using Weibull distribution and probability density function for ...

The main property of a discrete joint probability distribution can be stated as the sum of all non-zero probabilities is 1. The next line shows this as a formula. The marginal distribution of X can be ...

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 ...

Abstract: This paper investigates the probability density functions (PDFs) of the voltage deviations at the nodes of a low-voltage grid. The PDFs are obtained using a Monte Carlo simulation algorithm ...