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
k values and four different local density-based methods. It allows for referencing a random subsample
of 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.

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.

Lan-DeMets Method for Group Sequential Boundaries
Charlie Casper and Oscar A. Perez.  Based on FORTRAN program
ld98.
Computations related to group sequential boundaries.
Includes calculation of bounds using the Lan-DeMets alpha
spending function approach.

Charlie Casper and Oscar A. Perez.  Based on FORTRAN
program ld98.
Computations related to group sequential boundaries.
Includes calculation of bounds using the Lan-DeMets
alpha spending function approach.

Charlie Casper, Thomas Cook and Oscar A. Perez.  Based on FORTRAN
program ld98.
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>.

Longitudinal Drift-Diffusion Mixed Models (LDDMM)
c(person("Giorgio", "Paulon", email = "giorgio.paulon@utexas.edu",
role = c("aut", "cre")),
person("Abhra", "Sarkar", email = "abhra.sarkar@utexas.edu",
role = c("aut", "ctb")))
Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021).
Rcpp (>= 1.0.6), RcppProgress, rgen, gtools, LaplacesDemon,
dplyr, plyr, tidyr, ggplot2, latex2exp, reshape2, RColorBrewer
Giorgio Paulon [aut, cre],
Abhra Sarkar [aut, ctb]