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Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression

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  • Anabel Forte
  • Gonzalo Garcia‐Donato
  • Mark Steel

Abstract

In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R‐packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages.

Suggested Citation

  • Anabel Forte & Gonzalo Garcia‐Donato & Mark Steel, 2018. "Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression," International Statistical Review, International Statistical Institute, vol. 86(2), pages 237-258, August.
    • Handle: RePEc:bla:istatr:v:86:y:2018:i:2:p:237-258
    DOI: 10.1111/insr.12249
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    Cited by:

    1. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2019. "Searching The Us Fdi Determinants In The Eu: Is There A Euro Effect?," Working Papers 1916, Department of Applied Economics II, Universidad de Valencia.
    2. Sierra A. Bainter & Thomas G. McCauley & Mahmoud M. Fahmy & Zachary T. Goodman & Lauren B. Kupis & J. Sunil Rao, 2023. "Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 1032-1055, September.
    3. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2021. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian model averaging techniques," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(4), pages 881-926, November.
    4. Jose Olmo & Marcos Sanso‐Navarro, 2021. "Modeling the spread of COVID‐19 in New York City," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1209-1229, October.
    5. Rolando de la Cruz & Cristian Meza & Nicolás Narria & Claudio Fuentes, 2022. "A Bayesian Change Point Analysis of the USD/CLP Series in Chile from 2018 to 2020: Understanding the Impact of Social Protests and the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    6. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    7. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    8. Gonzalo García-Donato & María Eugenia Castellanos & Alicia Quirós, 2021. "Bayesian Variable Selection with Applications in Health Sciences," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    9. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model," Working Papers 2007, Department of Applied Economics II, Universidad de Valencia.
    10. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    11. Fouskakis, Dimitris & Ntzoufras, Ioannis & Perrakis, Konstantinos, 2020. "Variations of power-expected-posterior priors in normal regression models," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    12. Shahram Amini & Christopher F. Parmeter, 2020. "A Review of the ‘BMS’ Package for R with Focus on Jointness," Econometrics, MDPI, vol. 8(1), pages 1-21, February.
    13. Andrzej Cieślik & Oleg Gurshev & Sarhad Hamza, 2022. "Between the Eurozone crisis and the Brexit: the decade of British outward FDI into Europe," Empirical Economics, Springer, vol. 63(3), pages 1159-1192, September.
    14. Camarero, Mariam & Moliner, Sergi & Tamarit, Cecilio, 2021. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging," Japan and the World Economy, Elsevier, vol. 57(C).

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