The goal of this work is to examine emissivity signature variability (including particle size effects from the signature at the ground level (e.g., powers) into a detection context for study. We seek ...

Combines statistical methods with practical applications and computer software. Develops commonly used statistical models such as analysis of variance as well as linear and logistic regression. The ...

The six-vertex model is a paradigmatic framework in statistical mechanics, originally introduced to capture the essential physics of ice-type systems. By assigning one of six allowed configurations to ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

Although efficiency robust tests are preferred for genetic association studies when the genetic model is unknown, their statistical properties have been studied for different study designs separately ...

Enhance your skills in energy statistical analysis with our expanded three-day workshop. Dive deep into crucial topics like risk quantification and pricing models using practical exercises in Excel.

This paper addresses two closely related questions, "What is a statistical model?" and "What is a parameter?" The notions that a model must "make sense," and that a parameter must "have a well-defined ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Explore the principles of geospatial statistics and modeling. Meet the demand for geospatial professionals and big data analytics experts. Develop knowledge and skills in geospatial data analytics and ...