Extracting maximum likelihood estimates from a model_result

If you want to get the stats out-of a fitted model, use the evo.tabulate_stats() app.

We first fit a model.

Create and apply tabulate_stats app

tabulated is a tabular_result instance which, like other result types, has dict like behaviour. It also contains key/value pairs for each model parameter type.

Edge parameters

These are all parameters that differ between edges. Since the current model is time-homogeneous (a single rate matrix), only the table only has entries for the branch scalar (denoted “length”).

Note

Unless the model is time-reversible, the lengths in that table are not ENS (Kaehler et al). As we used a non-stationary nucleotide model in this example, the length values are a scalar used to adjust the matrices during optimisation.

Global parameters

In this example, these are the elements of the rate matrix.

Motif parameters

In the current example, these are estimates of the nucleotide probabilities in the unobserved ancestor.