Estimate Number of Latent Factors and Factor Matrix for Factor Analysis (esaBcv)
These functions estimate the latent factors of a given matrix, no matter it is high-dimensional or not. It tries to first estimate the number of factors using bi-cross-validation and then estimate the latent factor matrix and the noise variances. For more information about the method, see Art B. Owen and Jingshu Wang 2015 archived article on factor model (

Quantitative Analysis of Textual Data (quanteda)
A fast, flexible toolset for for the management, processing, and quantitative analysis of textual data in R.

A Collection of Small Text Corpora of Interesting Data (rcorpora)
A collection of small text corpora of interesting data. It contains all data sets from Some examples: names of animals: birds, dinosaurs, dogs; foods: beer categories, pizza toppings; geography: English towns, rivers, oceans; humans: authors, US presidents, occupations; science: elements, planets; words: adjectives, verbs, proverbs, US president quotes.