Principal Component Analysis as a Sanity Check for Bayesian
  Phylolinguistic Reconstruction
Yugo Murawaki
Bayesian approaches to reconstructing the evolutionary history of languages
rely on the tree model, which assumes that these languages descended from a
common ancestor and underwent modifications over time. However, this assumption
can be violated to different extents due to contact and other factors.
Understanding the degree to which this assumption is violated is crucial for
validating the accuracy of phylolinguistic inference. In this paper, we propose
a simple sanity check: projecting a reconstructed tree onto a space generated
by principal component analysis. By using both synthetic and real data, we
demonstrate that our method effectively visualizes anomalies, particularly in
the form of jogging.