Data Science: Theory and Applications: Volume 44
North-Holland (Publisher)
Published on 17. February 2021
Book
Hardback
348 pages
978-0-323-85200-5 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Undergraduates, graduates, academics and researchers in the field of Handbook of Statistics
Dimensions
Height: 229 mm
Width: 152 mm
Weight
700 gr
ISBN-13
978-0-323-85200-5 (9780323852005)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Persons
Content
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
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