GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Oxford :Oxford University Press, Incorporated,
    Keywords: Hurricanes -- Forecasting -- Statistical methods. ; R (Computer program language). ; Electronic books.
    Description / Table of Contents: Hurricane Climatology explains how to analyze and model hurricane data to better understand and predict present and future hurricane activity.
    Type of Medium: Online Resource
    Pages: 1 online resource (390 pages)
    Edition: 1st ed.
    ISBN: 9780199827640
    DDC: 551.5520285555
    Language: English
    Note: Cover -- Contents -- Preface -- Part One: Data, Statistics, and Software -- 1. Hurricanes, Climate, and Statistics -- 1.1. Hurricanes -- 1.2. Climate -- 1.3. Statistics -- 1.4. R -- 1.5. Organization -- 2. R Tutorial -- 2.1. Introduction -- 2.2. Data -- 2.3. Tables and Plots -- 3. Classical Statistics -- 3.1. Descriptive Statistics -- 3.2. Probability and Distributions -- 3.3. One-Sample Test -- 3.4. Wilcoxon Signed-Rank Test -- 3.5. Two-Sample Test -- 3.6. Statistical Formula -- 3.7. Two-Sample Wilcoxon Test -- 3.8. Compare Variances -- 3.9. Correlation -- 3.10. Linear Regression -- 3.11. Multiple Linear Regression -- 4. Bayesian Statistics -- 4.1. Learning about the Proportion of Landfalls -- 4.2. Inference -- 4.3. Credible Interval -- 4.4. Predictive Density -- 4.5. Is Bayes's Rule Needed? -- 4.6. Bayesian Computation -- 5. Graphs and Maps -- 5.1. Graphs -- 5.2. Time Series -- 5.3. Maps -- 5.4. Coordinate Reference Systems -- 5.5. Export -- 5.6. Other Graphic Packages -- 6. Data Sets -- 6.1. Best-Tracks Data -- 6.2. Annual Aggregation -- 6.3. Coastal County Winds -- 6.4. NetCDF Files -- Part Two: Models and Methods -- 7. Frequency Models -- 7.1. Counts -- 7.2. Environmental Variables -- 7.3. Bivariate Relationships -- 7.4. Poisson Regression -- 7.5. Model Predictions -- 7.6. Forecast Skill -- 7.7. Nonlinear Regression Structure -- 7.8. Zero-Inflated Count Model -- 7.9. Machine Learning -- 7.10. Logistic Regression -- 8. Intensity Models -- 8.1. Lifetime Highest Intensity -- 8.2. Fastest Hurricane Winds -- 8.3. Categorical Wind Speeds by County -- 9. Spatial Models -- 9.1. Track Hexagons -- 9.2. SST Data -- 9.3. SST and Intensity -- 9.4. Spatial Autocorrelation -- 9.5. Spatial Regression Models -- 9.6. Spatial Interpolation -- 10. Time Series Models -- 10.1. Time Series Overlays -- 10.2. Discrete Time Series -- 10.3. Change Points. , 10.4. Continuous Time Series -- 10.5. Time-Series Network -- 11. Cluster Models -- 11.1. Time Clusters -- 11.2. Spatial Clusters -- 11.3. Feature Clusters -- 12. Bayesian Models -- 12.1. Long-Range Outlook -- 12.2. Seasonal Model -- 12.3. Consensus Model -- 12.4. Space-Time Model -- 13. Impact Models -- 13.1. Extreme Losses -- 13.2. Future Wind Damage -- Appendix A. R Functions -- Appendix B. R Packages -- Appendix C. Data sets -- Bibliography -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- V -- W -- Z.
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...