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Statistical Methods in the Atmospheric Sciences
- 4th Edition - June 9, 2019
- Author: Daniel S. Wilks
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 5 8 2 3 - 4
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 6 5 2 7 - 0
Statistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of trying to meet the needs of students, researchers and operational practitio… Read more
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Request a sales quoteStatistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of trying to meet the needs of students, researchers and operational practitioners. This updated edition not only includes expanded sections built upon the strengths of the prior edition, but also provides new content where there have been advances in the field, including Bayesian analysis, forecast verification and a new chapter dedicated to ensemble forecasting.
- 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
Researchers and students in the atmospheric sciences, including meteorology, climatology, and other allied disciplines involving atmospheric data
- No. of pages: 840
- Language: English
- Edition: 4
- Published: June 9, 2019
- Imprint: Elsevier
- Paperback ISBN: 9780128158234
- eBook ISBN: 9780128165270
DW
Daniel S. Wilks
Daniel S. Wilks has been a member of the Atmospheric Sciences faculty at Cornell University since 1987, and is the author of Statistical Methods in the Atmospheric Sciences (2011, Academic Press), which is in its third edition and has been continuously in print since 1995. Research areas include statistical forecasting, forecast postprocessing, and forecast evaluation.
Affiliations and expertise
Department of Earth and Atmospheric Sciences, Cornell University, USA