Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Recent advances in high-throughput technologies have led to the emergence of systems
biology as a holistic science to achieve more precise modeling of complex diseases. Many …

Word clouds have emerged as a straightforward and visually appealing visualization
method for text. They are used in various contexts as a means to provide an overview by …

Statistical Foundations of Data Science gives a thorough introduction to commonly used
statistical models, contemporary statistical machine learning techniques and algorithms …

This paper comprehensively explores various influencing factors of crude oil price volatility
from four perspectives: commodity attributes, macroeconomics factors, geopolitical events …

Feature selection problems have been extensively studied in the setting of linear estimation
(eg LASSO), but less emphasis has been placed on feature selection for non-linear …

Motivated by research problems arising in the analysis of gut microbiome and metagenomic
data, we consider variable selection and estimation in high-dimensional regression with …

The construction industry is facing challenges from the hazardous nature of Ordinary
Portland Cement (OPC) production as one of the main contributors to global warming and …

This article focuses on a family of restricted latent structure models with wide applications in
psychological and educational assessment, where the model parameters are restricted via a …

Forward-backward selection is one of the most basic and commonly-used feature selection
algorithms available. It is also general and conceptually applicable to many different types of …