Bayesian prediction for stochastic processes

Simone Hermann
In many fields of statistical analysis, one is not only interested in estimation of model parameters, but in a prediction for future observations. For stochastic processes, on the one hand, one can be interested in the prediction for the further development of the current, i.e. observed, series. On the other hand, prediction for a new series can be of interest. This work presents two Bayesian prediction procedures based on the transition density of the Euler...
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