Statistical Modeling Using Local Gaussian Approximation
eBook - ePub

Statistical Modeling Using Local Gaussian Approximation

  1. 458 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Statistical Modeling Using Local Gaussian Approximation

About this book

Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution, perhaps, the most well-known and most used distribution in statistics, to a large class of non-Gaussian and nonlinear situations through local approximation. This extension enables the reader to follow new methods in assessing dependence and conditional dependence, in estimating probability and spectral density functions, and in discrimination. Chapters in this release cover Parametric, nonparametric, locally parametric, Dependence, Local Gaussian correlation and dependence, Local Gaussian correlation and the copula, Applications in finance, and more.Additional chapters explores Measuring dependence and testing for independence, Time series dependence and spectral analysis, Multivariate density estimation, Conditional density estimation, The local Gaussian partial correlation, Regression and conditional regression quantiles, and a A local Gaussian Fisher discriminant.- Reviews local dependence modeling with applications to time series and finance markets- Introduces new techniques for density estimation, conditional density estimation, and tests of conditional independence with applications in economics- Evaluates local spectral analysis, discovering hidden frequencies in extremes and hidden phase differences- Integrates textual content with three useful R packages

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Yes, you can access Statistical Modeling Using Local Gaussian Approximation by Dag Tjøstheim,Håkon Otneim,Bård Støve in PDF and/or ePUB format, as well as other popular books in Economics & Business Mathematics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Title of Book
  2. Cover image
  3. Title page
  4. Table of Contents
  5. Copyright
  6. Dedication
  7. Biography
  8. Preface
  9. Chapter 1 Introduction
  10. Chapter 2 Parametric, nonparametric, locally parametric
  11. Chapter 3 Dependence
  12. Chapter 4 Local Gaussian correlation and dependence
  13. Chapter 5 Local Gaussian correlation and the copula
  14. Chapter 6 Applications in finance
  15. Chapter 7 Measuring dependence and testing for independence
  16. Chapter 8 Time series dependence and spectral analysis
  17. Chapter 9 Multivariate density estimation
  18. Chapter 10 Conditional density estimation
  19. Chapter 11 The local Gaussian partial correlation
  20. Chapter 12 Regression and conditional regression quantiles
  21. Chapter 13 A local Gaussian Fisher discriminant
  22. Author index
  23. Subject index