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Statistical methods in the atmospheric sciences /
Praise for the First Edition:""I recommend this book, without hesitation, as either a reference or course text...Wilks' excellent book provides a thorough base in applied statistical methods for atmospheric sciences.""--BAMS (Bulletin of the American Meteorological Society)F...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Academic Press,
©2006.
|
| Edición: | 2nd ed. |
| Colección: | International geophysics series ;
v. 91. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Statistical Methods in the Atmospheric Sciences; Copyright Page; Contents; Preface to the First Edition; Preface to the Second Edition; PART I: Preliminaries; CHAPTER 1. Introduction; 1.1 What Is Statistics?; 1.2 Descriptive and Inferential Statistics; 1.3 Uncertainty about the Atmosphere; CHAPTER 2. Review of Probability; 2.1 Background; 2.2 The Elements of Probability; 2.3 The Meaning of Probability; 2.4 Some Properties of Probability; 2.5 Exercises; PART II: Univariate Statistics; CHAPTER 3. Empirical Distributions and Exploratory Data Analysis; 3.1 Background
- 3.2 Numerical Summary Measures3.3 Graphical Summary Techniques; 3.4 Reexpression; 3.5 Exploratory Techniques for Paired Data; 3.6 Exploratory Techniques for Higher-Dimensional Data; 3.7 Exercises; CHAPTER 4. Parametric Probability Distributions; 4.1 Background; 4.2 Discrete Distributions; 4.3 Statistical Expectations; 4.4 Continuous Distributions; 4.5 Qualitative Assessments of the Goodness of Fit; 4.6 Parameter Fitting Using Maximum Likelihood; 4.7 Statistical Simulation; 4.8 Exercises; CHAPTER 5. Hypothesis Testing; 5.1 Background; 5.2 Some Parametric Tests; 5.3 Nonparametric Tests
- 5.4 Field Significance and Multiplicity5.5 Exercises; CHAPTER 6. Statistical Forecasting; 6.1 Background; 6.2 Linear Regression; 6.3 Nonlinear Regression; 6.4 Predictor Selection; 6.5 Objective Forecasts Using Traditional Statistical Methods; 6.6 Ensemble Forecasting; 6.7 Subjective Probability Forecasts; 6.8 Exercises; CHAPTER 7. Forecast Verification; 7.1 Background; 7.2 Nonprobabilistic Forecasts of Discrete Predictands; 7.3 Nonprobabilistic Forecasts of Continuous Predictands; 7.4 Probability Forecasts of Discrete Predictands; 7.5 Probability Forecasts for Continuous Predictands
- 7.6 Nonprobabilistic Forecasts of Fields7.7 Verification of Ensemble Forecasts; 7.8 Verification Based on Economic Value; 7.9 Sampling and Inference for Verification Statistics; 7.10 Exercises; CHAPTER 8. Time Series; 8.1 Background; 8.2 Time Domain-I. Discrete Data; 8.3 Time Domain-II. Continuous Data; 8.4 Frequency Domain-I. Harmonic Analysis; 8.5 Frequency Domain-II. Spectral Analysis; 8.6 Exercises; PART III: Multivariate Statistics; CHAPTER 9. Matrix Algebra and Random Matrices; 9.1 Background to Multivariate Statistics; 9.2 Multivariate Distance; 9.3 Matrix Algebra Review
- 9.4 Random Vectors and Matrices9.5 Exercises; CHAPTER 10. The Multivariate Normal (MVN) Distribution; 10.1 Definition of the MVN; 10.2 Four Handy Properties of the MVN; 10.3 Assessing Multinormality; 10.4 Simulation from the Multivariate Normal Distribution; 10.5 Inferences about a Multinormal Mean Vector; 10.6 Exercises; CHAPTER 11. Principal Component (EOF) Analysis; 11.1 Basics of Principal Component Analysis; 11.2 Application of PCA to Geophysical Fields; 11.3 Truncation of the Principal Components; 11.4 Sampling Properties of the Eigenvalues and Eigenvectors