Data Science: Theory and Applications: Handbook of Statistics, cartea 44
C. R. Rao, Arni S.R. Srinivasa Raoen Limba Engleză Hardback – 17 feb 2021
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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Specificații
ISBN-13: 9780323852005
ISBN-10: 0323852009
Pagini: 348
Dimensiuni: 152 x 229 mm
Greutate: 0.64 kg
Editura: ELSEVIER SCIENCE
Seria Handbook of Statistics
ISBN-10: 0323852009
Pagini: 348
Dimensiuni: 152 x 229 mm
Greutate: 0.64 kg
Editura: ELSEVIER SCIENCE
Seria Handbook of Statistics
Public țintă
Undergraduates, graduates, academics and researchers in the field of Handbook of StatisticsCuprins
Section I: Animal Models and Ecological Large Data Methods
1. Statistical outline of animal home ranges: An application of set estimation
Amparo Baίllo 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 Baίllo 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