Predictive Statistics - Analysis and Inference Beyond Models

A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.

List of contents

Part I. The Predictive View: 1. Why prediction?; 2. Defining a predictive paradigm; 3. What about modeling?; 4. Models and predictors: a bickering couple; Part II. Established Settings for Prediction: 5. Time series; 6. Longitudinal data; 7. Survival analysis; 8. Nonparametric methods; 9. Model selection; Part III. Contemporary Prediction: 10. Blackbox techniques; 11. Ensemble methods; 12. The future of prediction; References; Index.

About the author

Bertrand S. Clarke is Chair of the Department of Statistics at the University of Nebraska, Lincoln. His research focuses on predictive statistics and statistical methodology in genomic data. He is a fellow of the American Statistical Association, serves as editor or associate editor for three journals, and has published numerous papers in several statistical fields as well as a book on data mining and machine learning.

Summary

Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and 'black box' settings, with computed examples.

Product details

• Authors: Bertrand S. Clarke, Bertrand S. (University of Nebraska Clarke, Jennifer L. Clarke, Jennifer L. (University of Nebraska Clarke, CLARKE BERTRAND
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 30.04.2018
• EAN: 9781107028289
• ISBN: 978-1-107-02828-9
• No. of pages: 656
• Series: Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Series in Statistica; Cambridge Series in Statistical and Probabilistic Mathematics
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries; MATHEMATICS / Probability & Statistics / General