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 ...

CEO of Paul M. Wendee & Associates, LLC; Publisher of the Intrinsic Value Wealth Report Newsletter; Founder of the Value Driver Institute. To make sound business and investment decisions, business ...

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 ...

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.

Dataset: survey ratings (1–10 scale) Target variable: Writing Methods: CUB (in R), Proportional Odds Model (in Python) Goal: Compare model adequacy and interpret ordinal responses ...

Abstract: Closed-loop control is widely adopted in industrial processes. It brings challenges for dynamic latent modeling and monitoring. Multirate process measurements in real applications even ...

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.

Determining whether a claimed invention is obvious under 35 U.S.C. § 103 often depends on whether the prior art provides a clear motivation for modifying existing knowledge. Central to this analysis ...

Abstract: In this article, a novel asymmetric-hybrid-pole variable flux memory machine (AHP-VFMM) is proposed and designed to realize satisfactory unintentional demagnetization (UD) withstand ...

The Basics of Returns-Based Style Analysis Fetching Data for Style Analysis Case Study: Looking for Investment Style Drift Unlock More Code Snippets for Rigorous Fund Evaluation Investors choose funds ...