Statistical convergence of random variables provides a rigorous framework to describe how sequences of random quantities approach limiting behaviour in probability, in distribution and in more refined ...

Probability underpins AI, cryptography and statistics. However, as the philosopher Bertrand Russell said, “Probability is the most important concept in modern science, especially as nobody has the ...

Abstract: Probability distributions are central tools for probabilistic modeling in data mining, and they lack in functional data analysis (FDA). In this paper we propose a probability distribution ...

Viewed creatively, the process for withdrawing required minimum distributions (RMDs) from an individual retirement account payable to a trust resembles a two-act play featuring “the twin pillars.” Act ...

Future events are far from certain in the business world. This is especially true for smaller businesses, which tend to have more volatility than larger organizations, or newer businesses without a ...

Forecasting for any small business involves guesswork. You know your business and its past performance, but you may not be comfortable predicting the future. Using Excel is a great way to perform what ...

dxxx(x,) returns the density or the value on the y-axis of a probability distribution for a discrete value of x pxxx(q,) returns the cumulative density function (CDF) or the area under the curve to ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

Abstract: In this letter, we derive the exact joint probability density function (pdf) of the amplitude and phase of the product of two correlated non-zero mean complex Gaussian random variables with ...