This repository collects materials and software for the method of Geometric Multivariate Analysis (GMA), which has been developed by Diwersy et al. (2014), Evert & Neumann (2017), and Neumann & Evert (2021).
A work in progress report on the mathematical background of GMA can be found in doc/. So far it contains a detailed exposition of the key technique of linear discriminant analysis (LDA) as well as some novel extensions. Further aspects of GMA will be described in future.
An experimental R package gmatools can be found in pkg/gmatools/, currently at version 0.1. While not available on CRAN yet, it can easily be installed from R with the help of devtools.
devtools::install_github("schtepf/GMA/pkg/gmatools")Diwersy, S., Evert, S., and Neumann, S. (2014). A weakly supervised multivariate approach to the study of language variation. In Szmrecsanyi, B. and Wälchli, B., editors, Aggregating Dialectology, Typology, and Register Analysis. Linguistic Variation in Text and Speech, Linguae et Litterae: Publications of the School of Language and Literature, Freiburg Institute for Advanced Studies, pages 174–204. De Gruyter, Berlin, Boston.
Evert, S. and Neumann, S. (2017). The impact of translation direction on characteristics of translated texts. A multivariate analysis for English and German. In De Sutter, G., Lefer, M.-A., and Delaere, I., editors, Empirical Translation Studies. New Theoretical and Methodological Traditions, TiLSM 300, pages 47–80. Mouton de Gruyter, Berlin. Online supplement: https://www.stephanie-evert.de/PUB/EvertNeumann2017/.
Neumann, S. and Evert, S. (2021). A register variation perspective on varieties of English. In Seoane, E. and Biber, D., editors, Corpus based approaches to register variation, chapter 6, pages 143–178. Benjamins, Amsterdam. Online supplement: https://www.stephanie-evert.de/PUB/NeumannEvert2021/.