Description: Sparse Graphical Modeling for High Dimensional Data by Faming Liang, Bochao Jia Estimated delivery 4-14 business days Format Hardcover Condition Brand New Description 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. Publisher Description 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; unified treatments for missing data and heterogeneous data; efficient methods for joint estimation of multiple graphical models; effective methods of high-dimensional variable selection; and effective methods of high-dimensional inference. The methods possess an embarrassingly parallel structure in performing conditional independence tests, and the computation can be significantly accelerated by running in parallel on a multi-core computer or a parallel architecture. This book is intended to serve researchers and scientists interested in high-dimensional statistics, and graduate students in broad data science disciplines.Key Features: A general framework for learning sparse graphical models with conditional independence tests Complete treatments for different types of data, Gaussian, Poisson, multinomial, and mixed data Unified treatments for data integration, network comparison, and covariate adjustment Unified treatments for missing data and heterogeneous data Efficient methods for joint estimation of multiple graphical models Effective methods of high-dimensional variable selectionEffective methods of high-dimensional inference Author Biography Dr. Faming Liang is Distinguished Professor of Statistics, Purdue University. Prior joining Purdue University in 2017, he held regular faculty positions in the Department of Biostatistics, University of Florida and Department of Statistics, Texas A&M University. Dr. Liang obtained his PhD degree from the Chinese University of Hong Kong in 1997. Dr. Liang is ASA fellow, IMS fellow, and elected member of International Statistical Association. Dr. Liang is also a winner of Youden Prize 2017. Dr. Liang has served as co-editor for Journal of Computational and Graphical Statistics, associate editor for multiple statistical journals, including Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Technometrics, Bayesian Analysis, and Biometrics, and editorial board member for Nature Scientific Report. Dr. Liang has published two books and over 130 journal/conference papers, which involve a variety of research fields such as Markov chain Monte Carlo, machine learning, bioinformatics, high-dimensional statistics, and big data computing.Dr. Bochao Jia is research scientist at Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana, U.S.A. Dr. Jia obtained his PhD degree from University of Florida in 2018. Dr. Jia has published quite a few papers on sparse graphical modelling. Details ISBN 0367183730 ISBN-13 9780367183738 Title Sparse Graphical Modeling for High Dimensional Data Author Faming Liang, Bochao Jia Format Hardcover Year 2023 Pages 130 Publisher Taylor & Francis Ltd GE_Item_ID:143005611; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 130.29 USD
Location: Calgary, Alberta
End Time: 2025-02-06T00:08:04.000Z
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ISBN-13: 9780367183738
Book Title: Sparse Graphical Modeling for High Dimensional Data
Publisher: CRC Press LLC
Subject: General
Publication Year: 2023
Number of Pages: 130 Pages
Publication Name: Sparse Graphical Modeling for High Dimensional Data : a Paradigm of Conditional Independence Tests
Language: English
Type: Textbook
Author: F. Liang, Bochao Jia
Subject Area: Mathematics
Format: Hardcover
