Georgia Secretary of State Brad Raffensperger's downplaying of a 2020 election blunder as a mere "clerical error" has done little to quiet a growing backlash within his own party. Far from accepting ...

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 ...

ABSTRACT: This study evaluates the reliability of North American Multi-Model Ensemble (NMME) models in forecasting monthly rainfall over the Kafue River Basin using a well-selected multi-model ...

Add a description, image, and links to the mean-square-error topic page so that developers can more easily learn about it.

Time series forecasting is essential for generating predictive insights across various domains, including healthcare, finance, and energy. This study focuses on forecasting patient health data by ...

Abstract: The paper proposes using alternative loss functions beyond mean squared error (MSE) for geoscience image regression tasks with neural networks. The ...

Abstract: Based on the Ziv-Zakai methodology to bound estimators, we derived an estimation bound able to predict the mean square error degradation due to model ...