vnc functions

is.sequence

A function to test the “evenness” of a sequence.

Description

A function to test the “evenness” of a sequence.

Usage

is.sequence(x, ...)

Arguments

Argument

Description

x

A vector of integers or number

Value

A logical value

vnc_clust

This function is based on the work of Greis and Hilpert (2012) for Variability-Based Neighbor Clustering. See here: https://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199922765.001.0001/oxfordhb-9780199922765-e-14

Description

The idea is to use hierarchical clustering to aid “bottom up” periodization of language change. The functions below are built on their original code here: http://global.oup.com/us/companion.websites/fdscontent/uscompanion/us/static/companion.websites/nevalainen/Gries-Hilpert_web_final/vnc.individual.html. However, rather than producing a plot, this function returns an hclust object. The advantage, is that an “hclust” object can be used to produce not only base R dendrograms, but can be passed to other functions for more detailed and controlled plotting.

Usage

vnc_clust(time, values, distance.measure = c("sd", "cv"))

Arguments

Argument

Description

time

A vector of sequential time intervals like years or decades

values

A vector containing normaized frequency counts

distance.measure

Indicating whether the standard deviation or coefficient of variation should be used in dinstance calculations

Value

An hclust object

vnc_scree

This is a simple function to return a scree plot based on the VNC algorithm.

Description

This is a simple function to return a scree plot based on the VNC algorithm.

Usage

vnc_scree(time, values, distance.measure = c("sd", "cv"))

Arguments

Argument

Description

time

A vector of sequential time intervals like years or decades

values

A vector containing normaized frequency counts

distance.measure

Indicating whether the standard deviation or coefficient of variation should be used in dinstance calculations

Value

A scree plot