# Bayesian forecasting

Discuss the differences between Bayesian forecasting and the incorportation of intervention analysis into the ARIMA model-building framework.

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Bayesian analysis is a statistical procedure, which endeavours to estimate parameters of an underlying distribution based on the observed distribution. We begin with a "prior distribution" which may be based on anything, including an assessment of the relative likelihoods of parameters or the results of non-Bayesian observations. In practice, it is common to assume a uniform distribution over the appropriate range of values for the prior distribution. Given the prior distribution, we collect data to obtain the observed distribution. Then likelihood of the observed distribution as a function of parameter values, ...

#### Solution Summary

The expert discusses the differences between Bayesian forecasting and the incorporation of intervention analysis into the ARIMA model-building frameworks.