B. K. Sahu

Time Series Modelling in Earth Sciences (eBook, PDF)

• Format: PDF

Produktbeschreibung

Including the latest theories and applications of time series modelling, this book is intended for students, faculties and professionals with a background in multivariate statistics. Highlighting linear methods to yield ARIMA, SARIMA models and their multivariate (vector) extensions, the text also draws attention to non-linear methods, as well as state-space, dynamic linear, wavelet, volatility and long memory models. Also included are several solved case studies and exercises from the fields of mining, ore genesis, earthquakes, and climatology.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 294
• Erscheinungstermin: 30. Juni 2021
• Englisch
• ISBN-13: 9781000443820
• Artikelnr.: 62113379

Autorenporträt

B.K. Sahu Department of Earth Sciences, IIT Bombay, Mumbai, India

Inhaltsangabe

1. Introduction 1.1 Dynamic Earth 1.2 Time/Spatial Series 1.3 Time Domain
Analysis 1.4 Frequency Domain Analysis 1.5 Spectral Analysis 1.6 Simple
Time Series Models 1.7 Model Validation and Inferences 1.8 State-Space
Model and Kalman Filtering 1.9 Procedures for Time Series Data Analysis
1.10 Examples 2. Stationary Univariate Time Series Models 2.1 Introduction
2.2 Stationary Processes 2.3 Identification 2.4 Forecasting 2.5 Purely
Seasonal ARMA Models ARMA(P, Q)s 2.6 Model Genesis and Realization 2.7
Examples 3. Non-Stationary Univariate Time Series Models 3.1 Introduction
3.2 Transformations for Stationarity 3.3 Unit Root Problems 3.4 Forecasting
ARIMA Models 3.5 SARIMA Models 4. Vector and Multidimensional Time Series
Analysis 4.1 Introduction 4.2 Multivariate ARMA Processes 4.3 Transfer
Function Models 4.4 Forecasting Techniques 4.5 Some Case Studies from
Economic Geology 5. Advanced Time Series Models 5.1 Introduction 5.2
State-Space Models 5.3 Dynamic Linear Modelling (DLM) with Switching 5.4
Non-Linear Models