Applying a discrete-time, non-stationary nucleotide model

We fit a discrete-time Markov nucleotide model. This corresponds to a Barry and Hartigan 1987 model.

Note

DLC stands for diagonal largest in column and the value is a check on the identifiability of the model. unique_Q is another identifiability check, but it not applicable to a discrete-time model and so remains as None.

Looking at the likelihood function, we see these maximum likelihood estimated values

Get a tree with branch lengths as paralinear

This is the only possible length metric for a discrete-time process.

Getting parameter estimates

For a discrete-time model, aside from the root motif probabilities, everything is edge specific. But note that the tabular_result has different keys from the continuous-time case, as demonstrated below.