- 272 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Skew-Normal Model Theories and Their Applications
About this book
The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest. This book is of academic value as it helps to establish a series of statistical inference theories and methods for skew-normal mixed effects models. On the applications side, it provides efficient methods and tools for practical data analysis in various fields including economics, finance, biology and medical science.
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Yes, you can access Skew-Normal Model Theories and Their Applications by Rendao Ye,Wenyan Zhu,Yue Qi,Kun Luo in PDF and/or ePUB format, as well as other popular books in Mathematics & Mathematical Analysis. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Preface
- Contents
- 1 Introduction
- 2 Preliminary Knowledge
- 3 Location Parameter of Skew-Normal Population
- 4 Common Location Parameter of Skew-Normal Populations
- 5 One-Way Classification Model with Skew-Normal Random Effects
- 6 Unbalanced One-Way Classification Model with Skew-Normal Random Effects
- 7 Skew-Normal Unbalanced Heteroscedastic One-Way Classification Random Effects Model
- 8 Skew-Normal Unbalanced Panel Model with One-Way Error Component
- 9 Skew-Normal Two-Way Classification Random Effects Model with Interaction
- 10 Skew-Normal Mixed Effects Model
- References
- Index