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Books on time series models deal mainly with models based on Box-Jenkins methodology which is generally represented by autoregressive integrated moving average models or some nonlinear extensions of these models, such as generalized autoregressive conditional heteroscedasticity models. Statistical inference for these models is well developed and commonly used in practical applications, due also to statistical packages containing time series analysis parts. The present book is based on regression models used for time series. These models are used not only for modeling mean values of observed time se­ ries, but also for modeling their covariance functions which are often given parametrically. Thus for a given finite length observation of a time series we can write the regression model in which the mean value vectors depend on regression parameters and the covariance matrices of the observation depend on variance-covariance parameters. Both these dependences can be linear or nonlinear. The aim of this book is to give an unified approach to the solution of statistical problems for such time series models, and mainly to problems of the estimation of unknown parameters of models and to problems of the prediction of time series modeled by regression models.

Time-series analysis --- Regression analysis --- Série chronologique --- Analyse de régression --- AA / International- internationaal --- 303.5 --- 304.0 --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Série chronologique --- Analyse de régression --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Probabilities. --- Statistics . --- Economics, Mathematical . --- Econometrics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Quantitative Finance. --- Economics --- Mathematical economics --- Econometrics --- Mathematics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Economics, Mathematical --- Statistics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk --- Methodology

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Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and nonstationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to nonlinear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

304.0 --- AA / International- internationaal --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Analyse : reeksen --- Mathematics. --- Computer software. --- Probabilities. --- Statistics. --- Econometrics. --- Mathematical Software. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Time-series analysis --- 519.55 --- tijdreeksanalyse --- 517 --- 519.2 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- 519.24 --- 519.24 Special statistical applications and models --- Special statistical applications and models --- Time-series analysis. --- Mathematical statistics. --- Économétrie --- Séries chronologiques --- Série chronologique --- EPUB-LIV-FT SPRINGER-B --- Distribution (Probability theory. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Économétrie. --- Séries chronologiques. --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Statistics . --- Software, Computer --- Computer systems --- Economics, Mathematical --- Statistics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk