The full text of this article

 

Predicting the present with Bayesian structural time series
by Steven L. Scott; Hal R. Varian
International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO), Vol. 5, No. 1/2, 2014

 

Abstract: This article describes a system for short term forecasting based on an ensemble prediction that averages over different combinations of predictors. The system combines a structural time series model for the target series with a regression component capturing the contributions of contemporaneous search query data. A spike-and-slab prior on the regression coefficients induces sparsity, dramatically reducing the size of the regression problem. Our system averages over potential contributions from a very large set of models and gives easily digested reports of which coefficients are likely to be important. We illustrate with applications to initial claims for unemployment benefits and to retail sales. Although our exposition focuses on using search engine data to forecast economic time series, the underlying statistical methods can be applied to more general short term forecasting with large numbers of contemporaneous predictors.

Online publication date: Thu, 20-Mar-2014

 

is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

 
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

 
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO):
Login with your Inderscience username and password:

 

    Username:        Password:         

Forgotten your password?


 
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

 
If you still need assistance, please email subs@inderscience.com