Semialgebraic Statistics and Latent Tree Models

This book introduces algebraic, combinatorial, and geometric methods for hidden tree models. It presents a focused introduction to some concepts in algebraic statistics and shows how the methods can be applied in statistics. The book also gives a broad overview of the current research on hidden tree models. Readers will gain a complete geometric and algebraic understanding of the models so that they can improve existing inference techniques.

Piotr Zwiernik is a Marie Sklodowska-Curie International Fellow in the Department of Mathematics at the University of Genoa. His research interests include statistical inference, graphical models with hidden variables, algebraic statistics, singular learning theory, time series analysis, and symbolic methods. He received a PhD in statistics from the University of Warwick.