| assign.plot.colors | Assign colors to samples |
| change.encoding | Change character encoding |
| check.encoding | Check character encoding in corpus folder |
| classify | Machine-learning supervised classification |
| crossv | Function to Perform Cross-Validation |
| define.plot.area | Define area for scatterplots |
| delete.markup | Delete HTML or XML tags |
| delete.stop.words | Exclude stop words (e.g. pronouns, particles, etc.) from a... |
| dist.cosine | Cosine Distance |
| dist.delta | Delta Distance |
| dist.entropy | Entropy Distance |
| dist.minmax | Min-Max Distance (aka Ruzicka Distance) |
| dist.simple | Cosine Distance |
| dist.wurzburg | Cosine Delta Distance (aka Wurzburg Distance) |
| galbraith | Table of word frequencies (Galbraith, Rowling, Coben,... |
| gui.classify | GUI for the function classify |
| gui.oppose | GUI for the function oppose |
| gui.stylo | GUI for stylo |
| imposters | Authorship Verification Classifier Known as the Imposters... |
| imposters.optimize | Tuning Parameters for the Imposters Method |
| lee | Table of word frequencies (Lee, Capote, Faulkner, Styron,... |
| load.corpus | Load text files |
| load.corpus.and.parse | Load text files and perform pre-processing |
| make.frequency.list | Make List of the Most Frequent Elements (e.g. Words) |
| make.ngrams | Make text n-grams |
| make.samples | Split text to samples |
| make.table.of.frequencies | Prepare a table of (relative) word frequencies |
| novels | A selection of 19th-century English novels |
| oppose | Contrastive analysis of texts |
| parse.corpus | Perform pre-processing (tokenization, n-gram extracting,... |
| parse.pos.tags | Extract POS-tags or Words from Annotated Corpora |
| performance.measures | Accuracy, Precision, Recall, and the F Measure |
| perform.culling | Exclude variables (e.g. words, n-grams) from a frequency... |
| perform.delta | Distance-based classifier |
| perform.impostors | An Authorship Verification Classifier Known as the Impostors... |
| perform.knn | k-Nearest Neighbor classifier |
| perform.naivebayes | Naive Bayes classifier |
| perform.nsc | Nearest Shrunken Centroids classifier |
| perform.svm | Support Vector Machines classifier |
| plot.sample.size | Plot Classification Accuracy for Short Text Samples |
| rolling.classify | Sequential machine-learning classification |
| rolling.delta | Sequential stylometric analysis |
| samplesize.penalize | Determining Minimal Sample Size for Text Classification |
| stylo | Stylometric multidimensional analyses |
| stylo.default.settings | Setting variables for the package stylo |
| stylo.network | Bootstrap consensus networks, with D3 visualization |
| stylo.pronouns | List of pronouns |
| txt.to.features | Split string of words or other countable features |
| txt.to.words | Split text into words |
| txt.to.words.ext | Split text into words: extended version |
| zeta.chisquare | Compare two subcorpora using a home-brew variant of Craig's... |
| zeta.craig | Compare two subcorpora using Craig's Zeta |
| zeta.eder | Compare two subcorpora using Eder's Zeta |
