A Bayesian approach to state space multivariate time series modeling
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Publication:1193512
DOI10.1016/0304-4076(92)90015-JzbMath0747.62095MaRDI QIDQ1193512
Jeffrey H. Dorfman, Arthur Havenner
Publication date: 27 September 1992
Published in: Journal of Econometrics (Search for Journal in Brave)
multivariate time seriesmodel specificationtime series modelinglinear systems theorymodel selection proceduresconstruction of optimal composite forecastsstate space modelling
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Economic time series analysis (91B84)
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Cites Work
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- A method for approximate representation of vector-valued time series and its relation to two alternatives
- System theoretic time series: An application to inventories and prices of California range cattle
- Estimation, filtering, and smoothing in state space models with incompletely specified initial conditions
- An instrumental variables interpretation of linear systems theory estimation
- Multivariate time series analysis with state space models
- Antithetic acceleration of Monte Carlo integration in Bayesian inference
- Bayesian forecasting and dynamic models
- Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes
- Estimating the dimension of a model
- Estimation of functions of population means and regression coefficients including structural coefficients. A minimum expected loss (MELO) approach
- Bayesian analysis of the federal reserve-MIT-Penn model's Almon lag consumption function
- Fully Bayesian analysis of ARMA time series models
- Statistical predictor identification
- A fundamental relation between predictor identification and power spectrum estimation
- State space modeling of multiple time series
- Bayesian Estimation and Prediction Using Asymmetric Loss Functions
- Minimum Expected Loss (MELO) Estimators for Functions of Parameters and Structural Coefficients of Econometric Models
- Recursive estimation of mixed autoregressive-moving average order
- A Bayesian extension of the minimum AIC procedure of autoregressive model fitting
- Forecasting and conditional projection using realistic prior distributions
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