A classification tree method that uses Uncorrelated Linear Discriminant Analysis (ULDA) for variable selection, split determination, and model fitting in terminal nodes.  It automatically handles missing values and offers visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2410.23147>.

Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial time series methods in a two-stage analysis to quantify dynamics in high-dimensional temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, whose relative proportions are modeled using generalized Bayesian time series models that include abrupt changepoints and smooth dynamics. The methods are described in Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>, Western and Kleykamp (2004) <doi:10.1093/pan/mph023>, Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) <doi:10.1002/ecy.2373>.

Tools to create an interactive web-based visualization of a
    topic model that has been fit to a corpus of text data using
    Latent Dirichlet Allocation (LDA). Given the estimated parameters of
    the topic model, it computes various summary statistics as input to
    an interactive visualization built with D3.js that is accessed via
    a browser. The goal is to help users interpret the topics in their
    LDA topic model.

Flexible procedures to compute local density-based outlier scores for ranking outliers.
  Both exact and approximate nearest neighbor search can be implemented, while also accommodating
  multiple neighborhood sizes and four different local density-based methods. It allows for
  referencing a random subsample of the input data or a user specified reference data set
  to compute outlier scores against, so both unsupervised and semi-supervised outlier
  detection can be implemented.

Computations related to group sequential boundaries.
    Includes calculation of bounds using the Lan-DeMets
    alpha spending function approach. Based on FORTRAN
        program ld98 implemented by Reboussin, et al. (2000) <doi:10.1016/s0197-2456(00)00057-x>.