You can use a VAR model with varied frequency data in a Bayesian context.

You can also use

MIxed Data Sampling (MIDAS) models, mixed frequency VARs, and mixed

frequency factor models

You can easily use various autoregressive models. I suggest you take a look on econometric books.

Yours,

Ehsan

To my view, an efficient way to formaly model such a type of problem is to consider Bayesian hierarchical modeling. I suggest you to read "Applied Bayesina Hierarchical Methods" by Gongdon or Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2004). Hierarchical modeling and analysis for spatial data. 2e éd., Chapman & Hall, Boca Raton, USA, 562 pages.

Best regards,

Luc

I would concur with Luc.  Spatial models have been developed by Noel Cressie and Christopher Wikle, amongst others, regarding which may be fit with Hierarchical Mixed Models (see Anthony Bryk and Steve Radebusch, Sage Publication, 2002).

There is a vast literature on these things as Bayesian Disease Mapping: Hierarchical Spatial analysis by Andrew Lawson  (2006) and others.  The USGS makes use of this material in much of their analysis as does the CDC.

  Regards,  

        Robert Yaffee