Book contents
- Frontmatter
- Contents
- Foreword
- Symbols
- Preface
- 1 Introduction
- Part One Historical and Theoretical Background
- Part Two Statistics and Applications to Data Analysis
- Part Three Complementary Topics
- 8 Further Applications
- 9 Transforms of Christoffel–Darboux Kernels
- 10 Spectral Characterization and Extensions of the Christoffel Function
- References
- Index
9 - Transforms of Christoffel–Darboux Kernels
from Part Three - Complementary Topics
Published online by Cambridge University Press: 31 March 2022
Book contents
- Frontmatter
- Contents
- Foreword
- Symbols
- Preface
- 1 Introduction
- Part One Historical and Theoretical Background
- Part Two Statistics and Applications to Data Analysis
- Part Three Complementary Topics
- 8 Further Applications
- 9 Transforms of Christoffel–Darboux Kernels
- 10 Spectral Characterization and Extensions of the Christoffel Function
- References
- Index
Summary
The stability of the Christoffel-Darboux kernel under small perturbations of the generating measure is established via precise quantitative bounds. Trace-class perturbations of the Hessenberg matrix attached to a 2D measure are linked to the asymptotic invariance of the Christoffel function, in an exact separation algorithm of outliers from clouds formed by bounded point evaluations for complex analytic functions.
Keywords
- Type
- Chapter
- Information
- The Christoffel–Darboux Kernel for Data Analysis , pp. 125 - 135Publisher: Cambridge University PressPrint publication year: 2022