A Parametric Approach to Nonparametric Statistics
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and...
Κύριοι συγγραφείς: | , |
---|---|
Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2018.
|
Έκδοση: | 1st ed. 2018. |
Σειρά: | Springer Series in the Data Sciences,
|
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- I. Introduction and Fundamentals
- Introduction
- Fundamental Concepts in Parametric Inference
- II. Modern Nonparametric Statistical Methods
- Smooth Goodness of Fit Tests
- One-Sample and Two-Sample Problems
- Multi-Sample Problems
- Tests for Trend and Association
- Optimal Rank Tests
- Efficiency
- III. Selected Applications
- Multiple Change-Point Problems
- Bayesian Models for Ranking Data
- Analysis of Censored Data
- A. Description of Data Sets.