LEADER 05180nam 22006495 450 001 9910349318203321 005 20200706230421.0 010 $a3-030-20790-0 024 7 $a10.1007/978-3-030-20790-8 035 $a(CKB)4100000009453372 035 $a(DE-He213)978-3-030-20790-8 035 $a(MiAaPQ)EBC5922010 035 $a(PPN)269151699 035 $a(EXLCZ)994100000009453372 100 $a20191004d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLinear Time Series with MATLAB and OCTAVE /$fby Víctor Gómez 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XVII, 339 p. 128 illus. in color.) 225 1 $aStatistics and Computing,$x1431-8784 311 $a3-030-20789-7 327 $aPreface -- Software Installation -- Stationarity, VARMA and ARIMA Models -- VARMAX and Transfer Function Models -- Unobserved Components in Univariate Series -- Spectral Analysis -- Computing Echelon Forms by Polynomial Methods -- Multivariate Structural Models -- Cointegrated VARMA Models -- Simulation of Common Univariate and Multivariate Models -- The State Space Model -- SSMMATLAB Examples by Subject -- Author Index -- Subject Index. 330 $aThis book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ?Multivariate Time Series With Linear State Space Structure?, by the same author, if they require more details. . 410 0$aStatistics and Computing,$x1431-8784 606 $aStatistics  606 $aEconometrics 606 $aComputer software 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 606 $aEconometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/W29010 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 606 $aMathematical Software$3https://scigraph.springernature.com/ontologies/product-market-codes/M14042 606 $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 615 0$aStatistics . 615 0$aEconometrics. 615 0$aComputer software. 615 14$aStatistics and Computing/Statistics Programs. 615 24$aEconometrics. 615 24$aStatistics for Social Sciences, Humanities, Law. 615 24$aMathematical Software. 615 24$aStatistics for Business, Management, Economics, Finance, Insurance. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 676 $a519.5 676 $a519.55 700 $aGómez$b Víctor$4aut$4http://id.loc.gov/vocabulary/relators/aut$0755989 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349318203321 996 $aLinear Time Series with MATLAB and OCTAVE$91732549 997 $aUNINA