The Skew-Normal and Related Families
eBook - PDF

The Skew-Normal and Related Families

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

The Skew-Normal and Related Families

Book details
Table of contents
Citations

About This Book

Interest in the skew-normal and related families of distributions has grown enormously over recent years, as theory has advanced, challenges of data have grown, and computational tools have made substantial progress. This comprehensive treatment, blending theory and practice, will be the standard resource for statisticians and applied researchers. Assuming only basic knowledge of (non-measure-theoretic) probability and statistical inference, the book is accessible to the wide range of researchers who use statistical modelling techniques. Guiding readers through the main concepts and results, it covers both the probability and the statistics sides of the subject, in the univariate and multivariate settings. The theoretical development is complemented by numerous illustrations and applications to a range of fields including quantitative finance, medical statistics, environmental risk studies, and industrial and business efficiency. The author's freely available R package sn, available from CRAN, equips readers to put the methods into action with their own data.

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Yes, you can access The Skew-Normal and Related Families by Adelchi Azzalini,Antonella Capitanio in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Title
  5. Imprints
  6. Contents
  7. Preface
  8. 1 Modulation of symmetric densities
  9. 2 The skew-normal distribution: probability
  10. 3 The skew-normal distribution: statistics
  11. 4 Heavy and adaptive tails
  12. 5 The multivariate skew-normal distribution
  13. 6 Skew-elliptical distributions
  14. 7 Further extensions and other directions
  15. 8 Application-oriented work
  16. Appendix A Main symbols and notation
  17. Appendix B Complements on the normal distribution
  18. Appendix C Notions on likelihood inference
  19. References
  20. Index