Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, traditional statistical models have struggled to interpret nonlinear, dynamic ...

Abstract: A revolutionary area of artificial intelligence called machine learning enables computers to learn from data and forecast without the need for explicit programming. A key component of ...

Research under classical statistics often relies on precise, determinate data to estimate population parameters. However, in certain situations, data may be indeterminate or imprecise. Neutrosophic ...

On Thursday, ESPN analyst David Hale ranked all 136 FBS football teams in tiers. Hale put BYU in the "Regression to the mean (the bad kind)" category. "If you look up and down the list of ...

The Texas Rangers have been one of the most disappointing teams in baseball this season. Coming into the year, many predicted they would challenge for the American League West title, returning to ...

Scholars trained in the use of factorial ANOVAs have increasingly begun using linear modelling techniques. When models contain interactions between continuous variables (or powers of them), it has ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

ABSTRACT: In this paper, a regression method of estimation has been used to derive the mean estimate of the survey variable using simple random sampling without replacement in the presence of ...

Abstract: For the online distributed estimation problem of time-varying parameters, we study a linear regression model with measurement noises over time-varying random graphs. We propose a distributed ...