Bayesian Forecasting
Bayesian Forecasting
In this paper Bayesian methods are applied to dynamical linear models \[ Y_ t=F_ t\theta_ t+v_ t,\quad \theta_ t=G_ t\theta_{t- 1}+w_ t, \] with normal distribution assumptions and dynamical generalized linear models with observations of the exponential family. The author gives an overview of some literature and applies the methods to the problem of describing the relationship between advertising and consumer behaviour.
- Roma Tre University Italy
Bayesian inference, unknown noise, disturbance covariance, Bayesian updating, linear time series models, forecasting, consumer behaviour, prediction, linear growth models, generalized linear models, Inference from stochastic processes and prediction, Time series, auto-correlation, regression, etc. in statistics (GARCH), autoregressive models, Linear inference, regression, dynamic regression, normal distribution assumptions, exponential family, dynamical linear models, discount Bayesian models, Applications of statistics to economics, advertising
Bayesian inference, unknown noise, disturbance covariance, Bayesian updating, linear time series models, forecasting, consumer behaviour, prediction, linear growth models, generalized linear models, Inference from stochastic processes and prediction, Time series, auto-correlation, regression, etc. in statistics (GARCH), autoregressive models, Linear inference, regression, dynamic regression, normal distribution assumptions, exponential family, dynamical linear models, discount Bayesian models, Applications of statistics to economics, advertising
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