ABSTRACT

Historical linguistics has witnessed an upsurge in quantitative corpus studies. The bulk of these studies involve the use of regression modelling. We point out a number of potential problems with this approach, and offer an alternative. For a multi-state language change, we propose a Markov model in continuous time. The major advantage of this technique, which has been used in medical contexts, is that it is especially geared towards dealing with time as a variable of interest, while it still allows one to look at the effect of several covariates. In this proof-of-concept article, we look at morphological shifts in preterites in Dutch, from 800ad to 2000ad (n = 14,314). This is a well-researched field, allowing us to investigate the performance of the multi-state Markov model.

摘要

历史语言学见证了定量语料库研究的热潮。这些研究的大部分涉及回归模型的使用。我们指出了这种方法的一些潜在问题，并提供了一种替代方法。对于多状态语言变化，我们提出了一个连续时间的马尔可夫模型。这种技术已在医学环境中使用，其主要优点是它特别适合将时间作为感兴趣的变量来处理，同时它仍然允许人们查看多个协变量的影响。在这篇概念验证文章中，我们研究了从公元 800年到公元 2000 年（ n = 14,314）的荷兰语旧词的形态变化。这是一个经过充分研究的领域，使我们能够研究多状态马尔可夫模型的性能。