Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests

This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison. Read More

This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison. Read Less

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  	This is a digital edition of this title. Rent eBook (2 Options) 180 Day Rental: $27.50 (Expires Aug 14, 2025) 365 Day Rental: $32.50 (Expires Feb 15, 2026) Buy eBook Lifetime Access: $49.99 Title: Sparse Graphical Modeling for High Dimensional Data by Faming Liang; Bochao Jia Publisher: Taylor & Francis Print ISBN: 9780367183738, 0367183730 eText ISBN: 9780429582905 Edition: 2023 1st edition Format: EPUB eBook	$27.50 Rent eBook This is a digital eBook Nothing will be shipped to you Works with web browsers and the VitalSource app on all Windows, Mac, Chromebook, Kindle Fire, iOS, and Android devices Most eBooks are returnable within 14 days of purchase Questions? See our eBook FAQ