The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Based upon ...

Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...

Muhammad Sumair, Tauseef Aized, Syed Asad Raza Gardezi, Muhammad Mahmood Aslam Bhutta, Syed Ubaid ur Rehman, Syed Muhammad Sohail Rehman Energy Exploration & Exploitation, Vol. 39, No. 5 (September ...

Density estimation methods often involve kernels, but there are advantages to using splines. Especially if the shape of the density is known to be decreasing, or unimodal, or bimodal, or if the ...

ABSTRACT: In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning ...

In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, ...

We discuss and analyze some recent literature that introduced pioneering methods in econophysics. In doing so, we review recent methods of estimating the volatility, volatility of volatility, and ...

Our development of a Fast (Mutual) Information Matching (FIM) of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a ...