Linear time series with MATLAB and OCTAVE. (2019)

• Record Type: Book
• Further Information: Note: Víctor Gómez.
• Authors: Gómez, Víctor
• Contents: Intro; Preface; Software Installation; References; Contents; 1 Quick Introduction to SSMMATLAB; 1.1 ARIMA Models; 1.2 Transfer Function Models; 1.3 Univariate Structural Models; 1.4 VARMA and VARMAX Models; 1.5 Innovations State Space Models and Likelihood Evaluation; Reference; 2 Stationarity, VARMA, and ARIMA Models; 2.1 Stationarity and VARMA Models; 2.1.1 Simulation of VARMA Models; 2.1.2 Sample Autocorrelations and PartialAutocorrelations; 2.1.3 VAR Models; 2.1.4 VAR Least Squares Estimation and Identification 2.1.5 Multiplicative VARMA Models: Preliminary Estimation and Model Simplification2.1.6 Multiplicative VARMA Model Identification; 2.1.7 Innovations State Space Models; 2.1.8 Fixing of Parameters; 2.1.9 Model Estimation Using the Kalman Filter; 2.1.10 Missing Observations; 2.1.11 Recursive Residuals and OLS Residuals; 2.1.12 Forecasting; 2.1.13 VARMA Models in Echelon Form; 2.1.14 VARMA Models in State Space Echelon Form; 2.1.15 Identification and Estimation of VARMA Models in Echelon Form; 2.2 ARMA and ARIMA Models; 2.2.1 State Space Form; 2.2.2 Complex Seasonal Patterns 2.2.3 Model Identification2.2.4 Model Estimation; 2.2.5 Fixing of Parameters; 2.2.6 Simplified ARIMA Estimation; 2.2.7 Missing Values; 2.2.8 Residuals; 2.2.9 Residual Diagnostics; 2.2.10 Tests for Residual Seasonality; 2.2.11 ARIMA Forecasting; 2.2.12 Forecasting Transformed Variables; 2.2.13 Trading Day, Easter, and Leap Year Effects; 2.2.14 Automatic Outlier Detection; 2.2.15 Automatic ARIMA Model Identification and Estimation; 2.2.16 Simplified Automatic ARIMA Specification and Estimation; References; 3 VARMAX and Transfer Function Models; 3.1 VARMAX Models 3.1.1 State Space Models With Inputs3.1.2 VARX Models; 3.1.3 VARX Identification and Least SquaresEstimation; 3.1.4 Identification and Estimation of VARMAX(p, q, r) Models; 3.1.5 VARMAX Models in Echelon Form; 3.1.6 VARMAX Models in State Space Echelon Form; 3.1.7 Identification and Estimation of VARMAX Models in Echelon Form; 3.1.8 VARMAX Estimation Using Regression Techniques: The Hannan-Rissanen Method; 3.1.9 Model Simplification Using Stepwise Regression; 3.1.10 The Conditional Method for VARMAXEstimation; 3.1.11 The Exact ML Method for VARMAX Estimation; 3.1.12 Forecasting VARMAX Models 3.2 Transfer Function Models3.2.1 TF Model Specification and Estimation; 3.2.2 TF Model Identification; 3.2.3 Automatic TF Model Identificationand Estimation; 3.2.4 Missing Values; 3.2.5 Residual Diagnostics, Forecasting, and Outliers; 3.2.6 Simplified Automatic TF Identification and Estimation; References; 4 Unobserved Components in Univariate Series; 4.1 Structural Models; 4.1.1 Model Specification and Estimation; 4.1.2 Simplified Model Specification and Estimation; 4.1.3 Model Identification; 4.1.4 Missing Values; 4.1.5 Residual Diagnostics and Forecasting; 4.1.6 Smoothing
• Publisher Details: Cham : Springer
• Publication Date: 2019
• Extent: 1 online resource (xvii, 339 pages), color illustrations
• Subjects: 519.5/5; Time-series analysis; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030207908; 3030207900
• Related ISBNs: 9783030207892
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (SpringerLink, viewed October 10, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.