Top Scoring Pair based methods for classification
This package is trying to implement Top Scoring Pair based
methods for classification including LDCA, TSP-tree, TSP-random
forest and TSP gradient boosting algorithm.

Dimension Reduction Methods for Multivariate Time Series
c(
person("Will", "Nicholson", email = "wbn8@cornell.edu", role = c("cre","aut")),
person("David", "Matteson", email = "matteson@cornell.edu", role = "aut"),
person("Jacob", "Bien", email = "bien@cornell.edu", role = "aut"))
Estimates VAR and VARX models with structured Lasso Penalties.
MASS, zoo, lattice, Rcpp, stats, utils, grDevices, graphics
Will Nicholson [cre, aut],
David Matteson [aut],
Jacob Bien [aut]

c(
person("Will", "Nicholson", email = "wbn8@cornell.edu", role = c("cre","aut")),
person("David", "Matteson", email = "matteson@cornell.edu", role = "aut"),
person("Jacob", "Bien", email = "bien@cornell.edu", role = "aut"),
person("Ines", "Wilms", email = "i.wilms@maastrichtuniversity.nl", role = "aut"))
Estimates VAR and VARX models with Structured Penalties using the methods developed by Nicholson et al (2017)<doi:10.1016/j.ijforecast.2017.01.003> and Nicholson et al (2020) <doi:10.48550/arXiv.1412.5250>.
MASS, zoo, Rcpp, stats, utils, grDevices, graphics, abind
knitr, rmarkdown, gridExtra, expm, MCS, quantmod, codetools
Will Nicholson [cre, aut],
David Matteson [aut],
Jacob Bien [aut],
Ines Wilms [aut]

Estimates VAR and VARX models with Structured Penalties.

Defines the functions used to compute the
bimodal index as defined by Wang et al. (2009)
<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730180/>.

Defines the functions used to compute the
bimodal index as defined by Wang et al. (2009)
<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730180/>,
<doi:10.4137/CIN.S2846>.

Calculation for Single Arm Group Sequential Test with Binary
Endpoint
c(
person(given = "Lei",
family = "Wang",
role = c("aut", "cre",'cph'),
email = "slimewanglei@163.com"),
person(given = "BeiGene, Ltd.",
family = "(Nasdaq: BGNE, HKEX: 06160)",
role = 'cph',
email = "https://www.beigene.com/"))
Consider an at-most-K-stage group sequential design with only an upper bound for the last analysis and non-binding lower bounds.With binary endpoint, two kinds of test can be applied, asymptotic test based on normal distribution and exact test based on binomial distribution. This package supports the computation of boundaries and conditional power for single-arm group sequential test with binary endpoint, via either asymptotic or exact test. The package also provides functions to obtain boundary crossing probabilities given the design.
Lei Wang [aut, cre, cph],
BeiGene, Ltd. (Nasdaq: BGNE, HKEX: 06160) [cph]