This one is focused on Bayesian inference. Bayes’ Theorem in combination with dynamic stochastic general equilibrium theory is really popular as a tool for monetary policy (where I first encountered its use) but also has applications in other areas such as biology and, in this case, people analytics.
Now, there are three R packages of interest. The first is a package oriented around the Markov Chain - MCMCpack (Martin, 2006), the second is deBInfer (Boersch-Supen, 2016), and most recently, there is INLA (Gomez-Rubio, 2020).More on these later.
References
Boersch-Supen, P. H., Ryan, S. J. and Johnson, Leah, R. (2016) “deBInfer: Bayesian Inference of dynamical models of biological systems in R”, Special Feature: Technological Advances at the Interface between Ecology and Statistics, 8(4), pp. 511-518, Available at: https://doi.org/10.1111/2041-210X.12679 (Accessed on 15 March 2024)
Gomez-Rubio, V. (2020) ‘Bayesian inference with INLA’, 1st Edition, New York: Chapman and Hall, Available at https://doi.org/10.1201/9781315175584 (Accessed on 15 March 2024)
Martin, A. D. and Quinn, Kevin. M. (2006) “Applied Bayesian Inference in R using MCMCpack”, R News, 6(1), pp. 2-7 – Available at: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/116223/rnews06.pdf?sequence=1 (Accessed on 15 March 2024)
-------
This post was written by Alfred Anate Mayaki, a student on the MSc in HRM. It was inspired by an Economic Issues article by Sarah Brown and John Sessions entitled “Absenteeism, Presenteeism, and Shirking”.