Relaxed clock models are fundamental in Bayesian clock dating, but a single distribution characterizing the clock variation is typically selected. Hence, I developed a new reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm for drawing posterior samples between the independent lognormal (ILN) and independent gamma rates (IGR) clock models. The ability of the rjMCMC algorithm to infer the true model was verified through simulations. I then applied the algorithm to the Mesozoic birds data previously analyzed under the white noise (WN) clock model. In comparison, averaging over the ILN and IGR models provided more reliable estimates of the divergence times and evolutionary rates. The ILN model showed slightly better fit than the IGR model and much better fit than the autocorrelated lognormal (ALN) clock model. When the data were partitioned, different partitions showed heterogeneous model fit for ILN and IGR clocks. The implementation provides a general framework for selecting and averaging relaxed clock models in Bayesian dating analyses.

Please see the Method section of the paper.

1. dataS1_simulations.zip: this zip archive contains
 (1) 100 birth-death trees generated by TreeSim in R (bd.trees and sim.bd.r); 
 (2) source code of the simulator (src/ folder);
 (3) shell script of each simulation setting in individual folders.
 
2. dataS2_birds.zip: this zip archive contains MrBayes commands for
 (1) the morphological data matrix (birds.nex);
 (2) stepping-stone sampling under the IGR clock model (ss_igr)
 (3) stepping-stone sampling under the ILN clock model (ss_igr)
 (4) stepping-stone sampling under the ALN(TK02) clock model (ss_aln)
 (5) rjMCMC sampling for unpartitioned data (td_mix)
 (6) rjMCMC sampling for partitioned data (td_p6_mix)