Opinion - My race isn’t your political forecast

The Supreme Court is being asked to decide whether race can continue to be used as a proxy for political identity in ...

Kayshon Boutte, Zay Flowers headline Week 9's Regression Files

Every week during the regular season I’ll highlight players whose usage and opportunity doesn’t quite match their production. That might look like a running back scoring touchdowns at an unsustainable ...
Devdiscourse

New AI forecasting model promises greater stability for Kenya’s volatile food prices

Kenya’s food markets are known for extreme volatility influenced by weather shocks, inflation, currency fluctuations, and ...
Scientific Research Publishing

Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning ()

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...
Finance Strategists on MSN

What to Know About the Methods and Applications of Financial Forecasting

Explore financial forecasting's importance in strategic decision-making, its methods, modern techniques, applications, and ...
IEEE

Interval Forecasting Using GEV Regression With Stochastic Search Variable Selection: A Simulation Study and Its Application to Forecast Imported Meat Price Range

Abstract: This study aims to forecast the price range, i.e., the interval forecast between the upper and lower bounds of prices, using Generalized Extreme Value Regression (GEVReg) as a robust tool ...
GitHub

Store-Sales-Time-Series-Forecasting---ML-Regression-Project

This project focuses on time series forecasting to predict store sales for Corporation Favorita, a large Ecuadorian-based grocery retailer. The goal is to build a model that accurately predicts the ...
Scientific Research Publishing

Wang, Y., Feng, L., Sui, X., Chu, J., & Mu, L. (2020). Nonlinear Regression Models for Agricultural Price Forecasting: A Comparative Study. Agricultural Systems, 180, 102-115.

ABSTRACT: This paper applies the novel adaptive learning methodology to forecast agricultural and energy prices in Greece’s volatile, data-scarce markets. We combine traditional ordinary least squares ...