- q.data
A single questioned or disputed text as a quanteda tokens object with the tokens being sentences (e.g. the output of tokenize_sents()).
- k.data
A known or undisputed corpus containing exclusively a single candidate author's texts as a quanteda tokens object with the tokens being sentences (e.g. the output of tokenize_sents()).
- ref.data
The reference dataset as a quanteda tokens object with the tokens being sentences (e.g. the output of tokenize_sents()).
- N
The order of the model. Default is 10.
- r
The number of iterations. Default is 30.
- output
A string detailing the file type of the colour-coded text output. Either "html" (default) or "latex".
- print
A string indicating the path and filename to save the colour-coded text file. If left empty (default), then nothing is printed.
- scale
A string indicating what scale to use to colour-code the text file. If "absolute" (default) then the raw \(\lambda_G\) is used; if "relative", then the z-score of \(\lambda_G\) over the Q data is used instead, thus showing relative importance.
- negative
Logical. If TRUE then negative values of \(\lambda_G\) are color-coded in blue, otherwise (default) only the positive values of \(\lambda_G\) are displayed in red. This only applies to HTML output.
- order.by
A string indicating the order of the output. If "importance" (default) then the output is ordered by sentence \(\lambda_G\) in descending order, otherwise the text is displayed and ordered as it appears.
- cores
The number of cores to use for parallel processing (the default is one).