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 36
... given in the last are actually replacement rates , and were converted to retention scores using Oswalt's inverse power function transformation ( 1975 ) . All values were given equal weight . A sixth term in the average indicated whether ...
... given in the last are actually replacement rates , and were converted to retention scores using Oswalt's inverse power function transformation ( 1975 ) . All values were given equal weight . A sixth term in the average indicated whether ...
Seite 166
... given in terms of the point process density fx for data - cognates and P ( D \ x , g , μ , M ( x ) > 1 ) ( the probability to realize data D given the tree , the data - cognate birth times , the death rate , and the requirement that ...
... given in terms of the point process density fx for data - cognates and P ( D \ x , g , μ , M ( x ) > 1 ) ( the probability to realize data D given the tree , the data - cognate birth times , the death rate , and the requirement that ...
Seite 174
... given the phylogenetic tree and a model of word evolution . The model of word evolution describes how various states ( words ) change over time within a speci- fied meaning . For any given meaning with k states or cognate sets , we can ...
... given the phylogenetic tree and a model of word evolution . The model of word evolution describes how various states ( words ) change over time within a speci- fied meaning . For any given meaning with k states or cognate sets , we can ...
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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Häufige Begriffe und Wortgruppen
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