Sparse Graphical Modeling for High Dimensional Data

Discover the cutting-edge insights in "Sparse Graphical Modeling for High Dimensional Data" by F. Liang, published by Taylor & Francis Ltd in 2023. This hardback edition spans 130 pages and offers a comprehensive framework for learning sparse graphical models through conditional independence tests.

Delve into detailed analyses covering various data types, including Gaussian, Poisson, multinomial, and mixed data. The book also provides unified approaches for covariate adjustments, data integration, and network comparison, making it an essential resource for researchers and practitioners in the field of mathematics and data science. Enhance your understanding of high-dimensional data analysis with this invaluable guide!