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Mathematical statistics --- Time-series analysis --- 519.55 --- kanstheorieën --- regressie-analyse --- tijdreeksanalyse --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities
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Mathematical statistics --- Time-series analysis --- Série chronologique --- 519.55 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities --- Série chronologique
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Mathematical statistics --- Time-series analysis --- Prediction theory --- Transfer functions --- Feedback control systems --- Mathematical models --- -519.55 --- Feedback mechanisms --- Feedback systems --- Automatic control --- Automation --- Discrete-time systems --- Adaptive control systems --- Feedforward control systems --- Forecasting theory --- Stochastic processes --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities --- Functions, Transfer --- Control theory --- 519.55 --- Feedback control systems - Mathematical models
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Stochastic processes --- Time-series analysis --- Markov processes --- R (Computer program language) --- Série chronologique --- Markov, Processus de --- R (Langage de programmation) --- 519.55 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Série chronologique
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This text provides an introduction to time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods. This is the first in a series of books designed to provide practitioners, researchers, and students with practical introductions to various topics in econometrics. - ;Providing a practical introduction to state space methods as applied to unobserved components time series models, also known as structural time series models, this book introduces time series analysis using state space methodology to readers who are n
State-space methods. --- Time-series analysis. --- Espace d'état, méthodes de l' --- Série chronologique --- Time-series analysis --- State-space methods --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- 519.55 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- System analysis --- Espace d'état, méthodes de l' --- Série chronologique --- time series analysis --- econometrie
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Time-series analysis --- Nonlinear theories --- 519.55 --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical analysis --- Mathematical physics --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- 303.7 --- #SBIB:303H510 --- 303.7 Analysetechnieken. Statistische analyse --(sociaal onderzoek) --- Analysetechnieken. Statistische analyse --(sociaal onderzoek) --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Nonlinear theories. --- Time-series analysis. --- Théories non linéaires --- Série chronologique
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Stochastic processes --- Mathematical statistics --- Brownian motion processes --- Time-series analysis --- 519.55 --- 519.21 --- 519.233.5 --- Wiener processes --- Brownian movements --- Fluctuations (Physics) --- Markov processes --- 519.233.5 Correlation analysis. Regression analysis --- Correlation analysis. Regression analysis --- 519.21 Probability theory. Stochastic processes --- Probability theory. Stochastic processes --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities
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Mathematical statistics --- Time-series analysis. --- Forecasting. --- Time-series analysis --- Forecasting --- AA / International- internationaal --- 303.0 --- 304.0 --- 304.5 --- 331.061 --- 519.55 --- Forecasts --- Futurology --- Prediction --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Techniek van de statistische-econometrische voorspellingen. Prognose in de econometrie. --- Economische vooruitzichten. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Techniek van de statistische-econometrische voorspellingen. Prognose in de econometrie --- Economische vooruitzichten --- Analyse des données --- Analyse des données
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Amongmanyexcitingdevelopmentsinstatisticsoverthelasttwodecades, nonlineartimeseriesanddata-analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In spite of the fact that the - plication of nonparametric techniques in time series can be traced back to the 1940s at least, there still exists healthy and justi?ed skepticism about the capability of nonparametric methods in time series analysis. As - thusiastic explorers of the modern nonparametric toolkit, we feel obliged to assemble together in one place the newly developed relevant techniques. Theaimofthisbookistoadvocatethosemodernnonparametrictechniques that have proven useful for analyzing real time series data, and to provoke further research in both methodology and theory for nonparametric time series analysis. Modern computers and the information age bring us opportunities with challenges. Technological inventions have led to the explosion in data c- lection (e.g., daily grocery sales, stock market trading, microarray data). The Internet makes big data warehouses readily accessible. Although cl- sic parametric models, which postulate global structures for underlying systems, are still very useful, large data sets prompt the search for more re?nedstructures,whichleadstobetterunderstandingandapproximations of the real world. Beyond postulated parametric models, there are in?nite other possibilities. Nonparametric techniques provide useful exploratory tools for this venture, including the suggestion of new parametric models and the validation of existing ones.
Time-series analysis --- Nonlinear theories --- 519.55 --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical analysis --- Mathematical physics --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- 303.0 --- 304.0 --- 305.971 --- AA / International- internationaal --- 519.246 --- 519.246 Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Speciale gevallen in econometrische modelbouw --- Nonlinear theories. --- Time-series analysis. --- Série chronologique --- Théories non linéaires --- EPUB-LIV-FT SPRINGER-B --- Probabilities. --- Statistics . --- Economics, Mathematical . --- Econometrics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Quantitative Finance. --- Economics, Mathematical --- Statistics --- Economics --- Mathematical economics --- Econometrics --- Mathematics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk --- Methodology
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The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.
519.246 --- Time-series analysis --- modeles economiques --- AA / International- internationaal --- 303.0 --- 304.0 --- 306.5 --- 519.55 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- economische modellen --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Statistische analyse (methodologie). --- 519.246 Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- Time-series analysis. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Statistische analyse (methodologie) --- Stochastic processes --- Statistical science --- Série chronologique --- Absolute summability. --- Autocovariance. --- Bartlett kernel. --- Block exogeneity. --- Cointegrating vector. --- Consumption spending. --- Cospectrum. --- Dickey-Fuller test. --- EM algorithm. --- Exchange rates. --- Filters. --- Fundamental innovation. --- Gamma distribution. --- Global identification. --- Gross national product. --- Hessian matrix. --- Inequality constraints. --- Invertibility. --- Jacobian matrix. --- Joint density. --- Khinchine's theorem. --- Kronecker product. --- Lagrange multiplier. --- Loss function. --- Mean-value theorem. --- Mixingales. --- Monte Carlo method. --- Newton-Raphson. --- Order in probability. --- Orthogonal. --- Permanent income. --- Quadrature spectrum. --- Recessions. --- Reduced form. --- Sample periodogram. --- Stock prices. --- Taylor series. --- Vech operator. --- Time series analysis
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