Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

How do subsystems of language evolve over time? It is commonly assumed that grammatical changes of language are slower than vocabulary changes. Using a Dirichlet process mixture model to analyze rates of language evolution in 81 Austronesian languages, the authors find that to the contrary, the grammatical features of language tend to change at a faster rate than basic vocabulary. Furthermore, their results show that grammatical features have higher rates of homoplasy, more frequent contact-induced change, and less deliberate differentiation than basic vocabulary.