
Statistical Methods in the Atmospheric Sciences
Resources
Description
Key Features
- Provides a strong, yet concise, introduction to applied statistics that is specific to atmospheric science
- Contains revised and expanded sections on nonparametric tests, test multiplicity and quality uncertainty descriptors
- Includes new sections on ANOVA, quantile regression, the lasso and other regularization methods, regression trees, changepoint detection, ensemble forecasting and exponential smoothing
Readership
Researchers and students in the atmospheric sciences, including meteorology, climatology, and other allied disciplines involving atmospheric data
Table of Contents
1. Introduction
2. Review of Probability
3. Empirical Distributions and Exploratory Data Analysis
4. Parametric Probability Distributions
5. Frequentist Statistical Inference
6. Bayesian Inference
7. Statistical Forecasting
8. Ensemble Forecasting
9. Forecast Verification
10. Time Series
11. Matrix Algebra and Random Matrices
12. Multivariate Normal Distribution
13. Principal Component (EOF) Analysis
14. Linear multivariate analysis of vector pairs: CCA, MCA, and RA
15. Discrimination and Classification
16. Cluster Analysis
Product details
- No. of pages: 840
- Language: English
- Copyright: © Elsevier 2019
- Published: June 9, 2019
- Imprint: Elsevier
- Paperback ISBN: 9780128158234
- eBook ISBN: 9780128165270
About the Author
Daniel Wilks
Affiliations and Expertise
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