Phylogenetic Methods and the Prehistory of LanguagesPeter Forster, Colin Renfrew McDonald Institute for Archaeological Research, 2006 - 198 Seiten Evolutionary ('phylogenetic') trees were first used to infer lost histories nearly two centuries ago by manuscript scholars reconstructing original texts. Today, computer methods are enabling phylogenetic trees to transform genetics, historical linguistics and even the archaeological study of artefact shapes and styles. But which phylogenetic methods are best suited to retracing the evolution of languages? And which types of language data are most informative about deep prehistory? In this book, leading specialists engage with these key questions. Essential reading for linguists, geneticists and archaeologists, these studies demonstrate how phylogenetic tools are illuminating previously intractable questions about language prehistory. This innovative volume arose from a conference of linguists, geneticists and archaeologists held at Cambridge in 2004. |
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Seite 124
... Markov random field together the resulting object is typically no longer a Markov random field . Thus taking a multi - state character and shoe - horning it into an off - the - shelf model from , say , biology by clumping states ...
... Markov random field together the resulting object is typically no longer a Markov random field . Thus taking a multi - state character and shoe - horning it into an off - the - shelf model from , say , biology by clumping states ...
Seite 126
... Markov model : Steel 1994 ) , the tree topology can be reconstructed with high probability from not that many ... Markov random field on the tree ( so we have a hidden Markov model ) . A discussion of these approaches with references to ...
... Markov model : Steel 1994 ) , the tree topology can be reconstructed with high probability from not that many ... Markov random field on the tree ( so we have a hidden Markov model ) . A discussion of these approaches with references to ...
Seite 175
... Markov chain Monte Carlo Markov chain Monte Carlo ( MCMC ) methods ( e.g. Geyer 1992 ; Gilks et al . 1996 ) as applied to phyloge- netic inference provide a computationally efficient way to estimate the posterior probability distribu ...
... Markov chain Monte Carlo Markov chain Monte Carlo ( MCMC ) methods ( e.g. Geyer 1992 ; Gilks et al . 1996 ) as applied to phyloge- netic inference provide a computationally efficient way to estimate the posterior probability distribu ...
Inhalt
ead25mole bio cam ac | 6 |
Malagasy Language as a Guide to Understanding Malagasy History | 11 |
Rapid Radiation Borrowing and Dialect Continua in the Bantu Languages | 19 |
Urheberrecht | |
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Africa Albanian algorithms Anatolian Archaeological assumptions Bantu languages Bantu trees Bastin Bayesian binary Biology borrowing branch lengths Cambridge Chapter clade cladistics classification coded cognate cognate class cognate sets comparative computational correspondences data set data-cognate dating dialects distribution divergence Dyen East Bantu edge English estimates evidence evolutionary example Figure Forster genetic Germanic glottochronology Gray & Atkinson Greek guages Historical Linguistics Hittite Holden homoplasy Indo-European languages Indo-Iranian inference innovations islands language data language evolution language family lexical evolution lexical replacement lexicostatistics likelihood Malagasy Markov matrix maximum parsimony McDonald Institute McMahon meaning Molecular morphological Mycenaean Neighbor-Net Nichols nodes Pagel parameters phonetic phonological characters phylogenetic methods phylogenetic trees phylogeny posterior probability probability problem Proto-Indo-European rates of lexical reconstruction relationships Renfrew reticulations root semantic slot similar split splits graph statistical subgroups Swadesh Swadesh list telic tion Tocharian verbs vocabulary Warnow word lists zone