Discover how precedent transaction analysis evaluates company value using past acquisition prices. Understand key factors, data sources, and its advantages and challenges.

Discover how the Bureau of Economic Analysis influences U.S. economic policy with vital reports on GDP, trade, and more, ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

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 ...

ABSTRACT: This study investigates the application of cumulative link models with alternative distributions (hyperbolic secant, Laplace, and Cauchy) to model ordinal outcomes of depressive severity ...

In this paper, we propose a user-friendly estimator to implement the method of difference-in-differences with ordinal ...

Since Bandt and Pompe’s seminal work, permutation entropy has been used in several applications and is now an essential tool for time series analysis. Beyond becoming a popular and successful ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

Introduction: Childhood vaccinations are crucial in safeguarding children from infectious diseases and are recognized as one of the most cost-effective public health interventions. However, children ...

This macro performs an ordinal cluster analysis on a given dataset. It processes the data to compute win fractions, conducts a mixed model regression on these win fractions, and fits a proportional ...

Factor analysis, a staple of correlational psychology, faces challenges with ordinal variables like Likert scales. The validity of traditional methods, particularly maximum likelihood (ML), is debated ...