A Review of the ‘BMS’ Package for R with Focus on Jointness

Shahram Amini and Christopher Parmeter
Additional contact information
Shahram Amini: Daniels College of Business, University of Denver, Denver, CO 80208, USA

Econometrics, 2020, vol. 8, issue 1, 1-21

Abstract: We provide a general overview of Bayesian model averaging (BMA) along with the concept of jointness. We then describe the relative merits and attractiveness of the newest BMA software package, BMS, available in the statistical language R to implement a BMA exercise. BMS provides the user a wide range of customizable priors for conducting a BMA exercise, provides ample graphs to visualize results, and offers several alternative model search mechanisms. We also provide an application of the BMS package to equity premia and describe a simple function that can easily ascertain jointness measures of covariates and integrates with the BMS package.

Keywords: bayesian model averaging; Zellner’s g -prior; BMS (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2225-1146/8/1/6/pdf (application/pdf)
https://www.mdpi.com/2225-1146/8/1/6/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:8:y:2020:i:1:p:6-:d:324495

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().