Victor Patrangenaru (Florida State University, Daniel E. Osborne (Florida Agricultural and Mechanical University
Nonparametric Statistics on Stratified Spaces and Their Applications in Object Data Analysis
Victor Patrangenaru (Florida State University, Daniel E. Osborne (Florida Agricultural and Mechanical University
Nonparametric Statistics on Stratified Spaces and Their Applications in Object Data Analysis
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This book, a follow-up of Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis is expanding the subject of data analysis on object spaces, to the case of metric spaces that have a smooth structure on an open dense subset only.
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This book, a follow-up of Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis is expanding the subject of data analysis on object spaces, to the case of metric spaces that have a smooth structure on an open dense subset only.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 208
- Erscheinungstermin: 6. Mai 2025
- Englisch
- Abmessung: 234mm x 156mm
- Gewicht: 453g
- ISBN-13: 9781138043138
- ISBN-10: 1138043133
- Artikelnr.: 72111222
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 208
- Erscheinungstermin: 6. Mai 2025
- Englisch
- Abmessung: 234mm x 156mm
- Gewicht: 453g
- ISBN-13: 9781138043138
- ISBN-10: 1138043133
- Artikelnr.: 72111222
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Vic Patrangenaru is a professor in the Statistics Department at Florida State University, Tallahassee, Florida, USA. He is an honored fellow of the Institute of Mathematical Statistics. His research encompasses analysis of complex data types, and the application of projective and differential geometry in various fields, including computer vision, medical imaging and phylogenetics. Throughout his career Dr. Patrangenaru, who guided many doctoral students, spearheaded the new area of Object Data Analysis. He added a new class to the Mathematics Subject Classification 2020 , 62R30 Statistics on Manifolds, which is currently in use by Mathematical Reviews and Zentralblatt für Mathematik Daniel E. Osborne is an associate professor in the Mathematics Department at Florida A&M University, Tallahassee, Florida, USA. As a trained Statistician and Data Science educator, he is dedicated to training student learners and promoting best practices in data literacy, statistical reasoning, data analysis, and data visualization skills among all learners, irrespective of their backgrounds, majors, or career paths.
Foreword Preface Part 1: Data and Preliminares for Analysis on Stratified
Spaces 1. Data of Complex Type 2. Review of Nonparametric Statistics on
Manifolds Part 2: Nonparametric Statistics on Stratified Spaces 3. Spaces
with a Manifold Stratification 4. Extrinsic Data Analysis on Stratified
Spaces 5. Intrinsic Sample Means on Tree Spaces 6. Central Limit Theorem
for Random Samples on a Graph 7. Analysis of Magnetic Resonance Angiography
Data 8. An Application to Phylogenies of SARS-CoV-2 Data Analysis Part 3:
Asymptotic Theory and Nonparametric Bootstrap on Special Stratified Spaces
9. CLT on Low Dimensional Stratified Spaces 10. Investigating Two Possible
Origins of SARS-CoV-2 11. Applications of Tree Spaces to Language Ancestry
12. 3D Face Differentiation from Digital Camera Images 13. Further
Directions in Statistics on Stratified Spaces Bibliography
Spaces 1. Data of Complex Type 2. Review of Nonparametric Statistics on
Manifolds Part 2: Nonparametric Statistics on Stratified Spaces 3. Spaces
with a Manifold Stratification 4. Extrinsic Data Analysis on Stratified
Spaces 5. Intrinsic Sample Means on Tree Spaces 6. Central Limit Theorem
for Random Samples on a Graph 7. Analysis of Magnetic Resonance Angiography
Data 8. An Application to Phylogenies of SARS-CoV-2 Data Analysis Part 3:
Asymptotic Theory and Nonparametric Bootstrap on Special Stratified Spaces
9. CLT on Low Dimensional Stratified Spaces 10. Investigating Two Possible
Origins of SARS-CoV-2 11. Applications of Tree Spaces to Language Ancestry
12. 3D Face Differentiation from Digital Camera Images 13. Further
Directions in Statistics on Stratified Spaces Bibliography
Foreword Preface Part 1: Data and Preliminares for Analysis on Stratified
Spaces 1. Data of Complex Type 2. Review of Nonparametric Statistics on
Manifolds Part 2: Nonparametric Statistics on Stratified Spaces 3. Spaces
with a Manifold Stratification 4. Extrinsic Data Analysis on Stratified
Spaces 5. Intrinsic Sample Means on Tree Spaces 6. Central Limit Theorem
for Random Samples on a Graph 7. Analysis of Magnetic Resonance Angiography
Data 8. An Application to Phylogenies of SARS-CoV-2 Data Analysis Part 3:
Asymptotic Theory and Nonparametric Bootstrap on Special Stratified Spaces
9. CLT on Low Dimensional Stratified Spaces 10. Investigating Two Possible
Origins of SARS-CoV-2 11. Applications of Tree Spaces to Language Ancestry
12. 3D Face Differentiation from Digital Camera Images 13. Further
Directions in Statistics on Stratified Spaces Bibliography
Spaces 1. Data of Complex Type 2. Review of Nonparametric Statistics on
Manifolds Part 2: Nonparametric Statistics on Stratified Spaces 3. Spaces
with a Manifold Stratification 4. Extrinsic Data Analysis on Stratified
Spaces 5. Intrinsic Sample Means on Tree Spaces 6. Central Limit Theorem
for Random Samples on a Graph 7. Analysis of Magnetic Resonance Angiography
Data 8. An Application to Phylogenies of SARS-CoV-2 Data Analysis Part 3:
Asymptotic Theory and Nonparametric Bootstrap on Special Stratified Spaces
9. CLT on Low Dimensional Stratified Spaces 10. Investigating Two Possible
Origins of SARS-CoV-2 11. Applications of Tree Spaces to Language Ancestry
12. 3D Face Differentiation from Digital Camera Images 13. Further
Directions in Statistics on Stratified Spaces Bibliography