Posterior parameter samples (3 clock partions)
An example dataset of posterior parameter samples resulting from a clock-based Bayesian inference analysis using the skyline fossilized birth–death process (FBD) tree model with Mr. Bayes after combining all parameter (.p) files into a single data frame with the
combine_log function. This particular example was produced by analyzing the data set with three morphological partitions from Simões & Pierce (2021).
A data frame with 4000 observations on several variables estimated for each generation during analysis. The number of variables depends on parameter set up, but for clock analyses with Mr. Bayes, will typically include the following:
A numeric vector for the generation number
A numeric vector for the natural log likelihood of the cold chain
A numeric vector for the natural log likelihood of the priors
A numeric vector for the total tree height (sum of all branch durations, as chronological units)
A numeric vector for total tree length (sum of all branch lengths, as accumulated substitutions/changes)
A numeric vector indicating the proportion of fossils recovered as ancestors
A numeric vector for the standard deviation of the lognormal distribution governing how much rates vary across characters for each data partition
A numeric vector for the rate multiplier parameter for each data partition
A numeric vector for net speciation estimates for each time bin
A numeric vector for relative extinction estimates for each time bin
A numeric vector for relative fossilization estimates for each time bin
A numeric vector for the variance on the base of the clock rate for each clock partition
A numeric vector for the base of the clock rate
Datasets like this one can be produced from parameter log (.p) files using
combine_log. The number of variables depends on parameter set up, but for clock analyses with Mr. Bayes, will typically include the ones above, possibly also including an
alpha for each partition, which contains the shape of the gamma distribution governing how much rates vary across characters (when shape of the distribution is unlinked across partitions). When using the traditional FBD model rather than the skyline FBD model used to produce this dataset, there will be only one column for each of
relative_fossilization. When using a single morphological partition, different columns may be present; see
posterior1p for an example with just one partition.
posterior1p for an example dataset of posterior parameter samples resulting from an analysis with 1 partition rather than 3.