We present ensemble Bayesian model averaging (EBMA) and illustrate its ability to aid scholars in the social sciences to make more accurate forecasts of future events. In essence, EBMA improves predic
Figure S2. Prior and posterior distributions of the number of rate shifts based on priors of 1, 5, and 10 shifts. Although the distribution of the number of shifts in the posterior is sensitive to the
Understanding the oscillating behaviors that govern organisms’ internal biological processes requires interdisciplinary efforts combining both biological and computer experiments, as the latter can co
