Statistical Learning in Genetics An Introduction Using R /
This book provides an introduction to computer-based methods for the analysis of genomic data. Breakthroughs in molecular and computational biology have contributed to the emergence of vast data sets, where millions of genetic markers for each individual are coupled with medical records, generating...
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| Главный автор: | |
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| Соавтор: | |
| Формат: | Электронный ресурс eКнига |
| Язык: | английский |
| Опубликовано: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Редактирование: | 2nd ed. 2025. |
| Серии: | Statistics for Biology and Health,
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| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/978-3-031-86274-8 |
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Оглавление:
- - 1. Overview
- Part I: Fitting Likelihood and Bayesian Models
- 2. Likelihood
- 3. Computing the Likelihood
- 4. Bayesian Methods
- 5. McMC in Practice
- Part II: Prediction
- 6. Fundamentals of Prediction
- 7. Shrinkage Methods
- 8. Digression on Multiple Testing: False Discovery Rates
- 9. Binary Data
- 10. Bayesian Prediction and Model Checking
- 11. Nonparametric Methods: A Selected Overview
- Part III: Exercises and Solutions
- 12. Exercises
- 13. Solution to Exercises.