Data Science: Theory and Applications (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more.

Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods.

• Provides the authority and expertise of leading contributors from an international board of authors
• Presents the latest release in the Handbook of Statistics series
• Updated release includes the latest information on Data Science: Theory and Applications

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 348
• Erscheinungstermin: 12. Februar 2021
• Englisch
• ISBN-13: 9780323852012
• Artikelnr.: 61681870

Autorenporträt

Arni S.R. Srinivasa Rao works in pure mathematics, applied mathematics, probability, and artificial intelligence and applications in medicine. He is a Professor at the Medical College of Georgia, Augusta University, U.S.A, and the Director of the Laboratory for Theory and Mathematical Modeling housed within the Division of Infectious Diseases, Medical College of Georgia, Augusta, U.S.A. Previously, Dr. Rao conducted research and/or taught at Mathematical Institute, University of Oxford (2003, 2005-07), Indian Statistical Institute (1998-2002, 2006-2012), Indian Institute of Science (2002-04), University of Guelph (2004-06). Until 2012, Dr. Rao held a permanent faculty position at the Indian Statistical Institute. He has won the Heiwa-Nakajima Award (Japan) and Fast Track Young Scientists Fellowship in Mathematical Sciences (DST, New Delhi). Dr. Rao also proved a major theorem in stationary population models, such as, Rao's Partition Theorem in Populations, Rao-Carey Theorem in stationary populations, and developed mathematical modeling-based policies for the spread of diseases like HIV, H5N1, COVID-19, etc. He developed a new set of network models for understanding avian pathogen biology on grid graphs (these were called chicken walk models), AI Models for COVID-19 and received wide coverage in the science media. Recently, he developed concepts such as "Exact Deep Learning Machines?, and "Multilevel Contours? within a bundle of Complex Number Planes.

Inhaltsangabe

Section I: Animal Models and Ecological Large Data Methods

1. Statistical outline of animal home ranges: An application of set estimation
Amparo Ba?llo and José Enrique Chacón

2. Modeling extreme climatic events using the generalized extreme value (GEV) distribution
Diana Rypkema and Shripad Tuljapurkar

Section II: Engineering Sciences Data

3. Blockchain technology: Theory and practice
Srikanth Cherukupally

4. Application of data handling techniques to predict pavement performance
Sireesh Saride, Pranav R.T. Peddinti and B. Munwar Basha

Section III: Statistical Estimation Designs: fractional fields, biostatistics and non-parametrics

5. On the usefulness of lattice approximations for fractional Gaussian fields
Somak Dutta and Debashis Mondal

6. Estimating individual-level average treatment effects: Challenges, modeling approaches, and practical applications
Victor B. Talisa and Chung-Chou H. Chang

7. Nonparametric data science: Testing hypotheses in large complex data
Sunil Mathur

Section IV: Network Models and COVID-19 modeling

8. Network models in epidemiology
Tae Jin Lee, Masayuki Kakehashi and Arni S.R. Srinivasa Rao

9. Modeling and forecasting the spread of COVID-19 pandemic in India and significance of lockdown: A mathematical outlook
Brijesh P. Singh

10. Mathematical modeling as a tool for policy decision making: Applications to the COVID-19 pandemic
J.Panovska-Griffiths, C.C. Kerr, W. Waites and R.M. Stuart