245 Pages
by
Chapman & Hall
246 Pages
by
Chapman & Hall
245 Pages
by
Chapman & Hall
Also available as eBook on:
Semialgebraic Statistics and Latent Tree Models explains how to analyze statistical models with hidden (latent) variables. It takes a systematic, geometric approach to studying the semialgebraic structure of latent tree models. The first part of the book gives a general introduction to key concepts in algebraic statistics, focusing on methods that are helpful in the study of models with... Read more
Introduction. Semialgebraic statistics: Algebraic and analytic geometry. Algebraic statistical models. Tensors, moments, and combinatorics. Latent tree graphical models: Phylogenetic trees and their models. The local geometry. The global geometry. Gaussian latent tree models.
Biography
Piotr Zwiernik is a Marie Skłodowska-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.
