Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Introduction: Causal inference of athletic injuries provides the critical foundations for the development of effective prevention strategies. In recent years, the directed acyclic graph model (DAG) ...

If you’re new to Python, one of the first things you’ll encounter is variables and data types. Understanding how Python handles data is essential for writing clean, efficient, and bug-free programs.

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

Abstract: This paper introduces a novel framework for Archetypal Analysis (AA) tailored to ordinal data, particularly from questionnaires. Unlike existing methods, the proposed method, Ordinal ...

ABSTRACT: Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure.

Neurointervention has seen significant advancements in recent decades with the adoption of myriad new technologies and techniques. Initially reliant on case reports and small case series, we now ...