fDMA: Dynamic Model Averaging and Dynamic Model Selection for Continuous Outcomes

Allows to estimate dynamic model averaging, dynamic model selection and median probability model. The original methods are implemented, as well as, selected further modifications of these methods. In particular the user might choose between recursive moment estimation and exponentially moving average for variance updating. Inclusion probabilities might be modified in a way using 'Google Trends'. The code is written in a way which minimises the computational burden (which is quite an obstacle for dynamic model averaging if many variables are used). For example, this package allows for parallel computations and Occam's window approach. The package is designed in a way that is hoped to be especially useful in economics and finance. Main reference: Raftery, A.E., Karny, M., Ettler, P. (2010) <doi:10.1198/TECH.2009.08104>.

Getting started

Package details

AuthorKrzysztof Drachal [aut, cre] (Faculty of Economic Sciences, University of Warsaw, Poland)
MaintainerKrzysztof Drachal <[email protected]>
URL https://CRAN.R-project.org/package=fDMA
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the fDMA package in your browser

Any scripts or data that you put into this service are public.

fDMA documentation built on Sept. 30, 2018, 1:03 a.m.