AbstractThis paper deals with the problem of linguistic homoplasy (parallel or backward development), how it can be detected, what kinds of linguistic homoplasy can be distinguished and which varieties of the phenomenon are the most deleterious for the reconstruction of language phylogeny. It is proposed that language phylogeny reconstruction should consist of two main stages. Firstly, a strict consensus tree should be built on the basis of high-quality input data elaborated with the help of the main phylogenetic methods (such as Neighbor-joining, Bayesian MCMC, and Maximum parsimony), and ancestral character states, allowing us to reveal a certain number of homoplastic characters. Secondly, after the detected instances of homoplasy are eliminated from the input matrix, the consensus tree is to be compiled again. It is expected that after homoplastic optimization it will be possible to better resolve individual “problem clades”, and generally the homoplasy-optimized phylogeny should be more robust than the tree constructed initially. The proposed procedure is tested on the 110-item Swadesh wordlists of the Lezgian and Tsezic groups. The Lezgian and Tsezic results generally support theoretical expectations. The MLN (minimal lateral network) method, currently implemented in the LingPy software, is a helpful tool for the detection of linguistic homoplasy.
Bayesian Estimation of the Functional Spatial Lag Model
