Statistical Methods in the Atmospheric Sciences

Informationen zum Autor Daniel S. Wilks is a Professor Emeritus at Cornell University and has been a Member of the Atmospheric Sciences faculty since 1987. His research focuses on the application of statistical methods for the quantification and analysis of uncertainty in meteorological and climatological data and forecasts. Dr. Wilks has taught courses on statistics in the atmospheric sciences and has been an Author or Coauthor of more than 100 peer-reviewed research articles. Klappentext This revised and expanded text explains the latest statistical methods that are being used to describe, analyze, test, and forecast atmospheric data. It features numerous worked examples, illustrations, equations, and exercises with separate solutions. The book will help advanced students and professionals understand and communicate what their data sets have to say, and make sense of the scientific literature in meteorology, climatology, and related disciplines. Zusammenfassung Explains the various statistical methods that are being used to describe! analyze! test and forecast atmospheric data. This title helps advanced students and professionals understand and communicate what their data sets have to say! and make sense of the scientific literature in meteorology! climatology! and related disciplines. Inhaltsverzeichnis I Preliminaries 1. Introduction2. Review of Probability II Univariate Statistics 3. Empirical Distributions and Exploratory Data Analysis4. Parametric Probability Distributions5. Frequentist Statistical Inference6. Bayesian Inference7. Statistical Forecasting8. Forecast Verification9. Time Series III Multivariate Statistic 10. Matrix Algebra and Random Matrices11. The Multivariate Normal (MVN) Distribution12. Principal Component (EOF) Analysis13. Canonical Correlation Analysis (CCA)14. Discrimination and Classification15. Cluster Analysis AppendixA. Example Data SetsB. Probability TablesC. Answers to Exercises ...

Détails du produit

• Auteurs: Daniel S. Wilks, Daniel S. (Department of Earth and Atmospheric Sciences Wilks, Daniel S Wilks, Wilks Daniel S.
• Edition: Academic Press London
• Contenu: Livre
• Forme du produit: Livre Relié
• Date de parution: 30.09.2011
• Catégorie: Sciences naturelles, médecine, it, technique > Sciences de la Terre > Géologie
• EAN: 9780123850225
• ISBN: 978-0-12-385022-5
• Nombre de pages: 704
• Thème: Academic Press; International Geophysics; Academic Press; International Geophysics; International Geophysics (Hard > 100
• Catégories: Chaos, skill, Resistance, Meteorologie und Klimatologie (Klimaforschung), Matrix, REGRESSION, MATHEMATICS / Probability & Statistics / General, Geologie und die Lithosphäre, SCIENCE / Earth Sciences / Meteorology & Climatology, Correlation, EDA, Bias, k-means, Maximum likelihood, probability, MOS, Meteorology & climatology, Vector, Meteorology and climatology, Probability & statistics, Harmonic analysis, Probability and statistics, Uncertainty, Eigenvalues, Markov chain, logistic regression, generalized linear models, Robustness, bayesian statistics, statistical significance, accuracy, Persistence, Hypothesis tests, Confidence intervals, Hierarchical Clustering, eigenvectors, Power spectrum, Sampling distribution, method of moments, Forecast Evaluation, Multivariate normal distribution, stationarity, canonical variates, random-number generation, singular spectrum analysis, multivariate stochastic simulation, Ward's method, predictive distribution, dendrogram, autoregression, empirical orthogonal functions, Posterior Distribution, Fisher's linear discriminant, rotated PCA, subjective forecasting, singular-value decomposition, canonical vectors, PCA truncation, maximum covariance analysis, continuous and discrete distributions, Mahalanobis distance, multiple discriminant analysis, prior distribution, field significance, Markov-chain Monte Carlo (MCMC), re-expression, ensemble forecasting, Hotelling T 2, diagnostic verification, Relative Frequency