Continuous Variable: can take on any value between two specified values. Obtained by measuring. Discrete Variable: not continuous variable (cannot take on any value between two specified values).

A continuous random variable X follows a normal distribution, denoted as $X \sim \mathcal{N}(\mu,,\sigma^{2})$. The normal distribution is characterized by its bell ...

Expert judgment elicitation is often required in probabilistic decision making and the evaluation of risk. One measure of the quality of probability distributions given by experts is calibration-the ...

A continuous random variable is a type of variable that can take on any value within a given range. Unlike discrete random variables, which have a countable number of outcomes, continuous random ...

Abstract: Astract- This paper presents a new energy-based continuous time series probability model that has stochastic process in its latent dynamics. Because the model assuming its output is used for ...

Abstract: Ong and Ho developed optimal linear index codes for single uniprior index coding problems (ICPs) by finding a spanning tree for each strongly connected component of their information-flow ...