Introduction to time series modeling with applications in R. (2020)

• Record Type: Book
• Further Information: Note: Genshiro Kitagawa.
• Authors: Kitagawa, G (Genshiro), 1948-
• Contents: 1 Introduction and Preparatory Analysis 1.1 Time Series Data 1.2 Classification of Time Series 1.3 Objectives of Time Series Analysis 1.4 Pre-processing of Time Series 1.4.1 Transformation of variables 1.4.2 Differencing 1.4.3 Month-to-month basis and year-over-year 1.4.4 Moving average 1.5 Organization of This Book 2 The Covariance Function 2.1 The Distribution of Time Series and Stationarity 2.2 The Autocovariance Function of Stationary Time Series 2.3 Estimation of the Autocovariance Function 2.4 Multivariate Time Series and Scatterplots 2.5 Cross-covariance Function and Cross-correlation Function 3 The Power Spectrum and the Periodogram 3.1 The Power Spectrum 3.2 The Periodogram 3.3 Averaging and Smoothing of the Periodogram 3.4 Computational Method of Periodogram 3.5 Computation of the Periodogram by Fast Fourier Transform 4 Statistical Modeling 4.1 Probability Distributions and Statistical Models 4.2 K-L Information and Entropy Maximization Principle 4.3 Estimation of the K-L Information and the Log-likelihood 4.4 Estimation of Parameters by the Maximum Likelihood Method 4.5 AIC (Akaike Information Criterion) 4.5.1 Evaluation of C 1 4.5.2 Evaluation of C 3 4.5.3 Evaluation of C 2 4.5.4 Evaluation of C and AIC 4.6 Transformation of Data 5 The Least Squares Method 5.1 Regression Models and the Least Squares
• Edition: Second edition
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 519.55; State-space methods; Time-series analysis
• Languages: English
• ISBNs: 9780429582622; 9780429584527; 9780429580406; 9780429197963
• Related ISBNs: 9780367187330
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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