c(
person("Maximilian M.", "Rabe", email = "maximilian.rabe@uni-potsdam.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2556-5644")),
person("Reinhold", "Kliegl", email = "kliegl@uni-potsdam.de", role = c("aut"), comment = c(ORCID = "0000-0002-0180-8488")),
person("Daniel J.", "Schad", email = "schad@uni-potsdam.de", role = c("aut"), comment = c(ORCID = "0000-0003-2586-6823")))

knitr, rmarkdown, tidyverse, jsonlite, writexl

Sample Size Calculation of Various Study Designs
Different sample size calculations with different study designs.
These techniques are explained by Chow (2007)
<doi:10.1201/9781584889830>.
c(person(("Atanu"), "Bhattacharjee",
email="atanustat@gmail.com",
role=c("aut", "cre","ctb")),
person(("Rajashree"), "Dey", role=c("aut","ctb")),
person(("Soutik"), "Halder", role=c("aut","ctb")),
person(("Akash"), "Pawar", role=c("aut","ctb")))
Atanu Bhattacharjee [aut, cre, ctb],
Rajashree Dey [aut, ctb],
Soutik Halder [aut, ctb],
Akash Pawar [aut, ctb]

Desirabiliy Function Optimization and Ranking
S3 classes for multivariate optimization using the desirability function by Derringer and Suich (1980)

S3 classes for multivariate optimization using the
desirability function by Derringer and Suich (1980)

Desirability Function Optimization and Ranking
S3 classes for multivariate optimization using the desirability function by Derringer and Suich (1980).

Function Optimization and Ranking via Desirability Functions

Harrington and Derringer-Suich type desirability functions
Heike Trautmann <trautmann@statistik.tu-dortmund.de> and Detlef
Steuer <detlef.steuer@hsu-hamburg.de> and Olaf Mersmann
<olafm@statistik.tu-dortmund.de>

Heike Trautmann, Detlef Steuer and Olaf Mersmann

c(
person("Robert", "Adamek", email="robertadamek94@gmail.com", role=c("cre", "aut")),
person("Stephan", "Smeekes", email = "s.smeekes@maastrichtuniversity.nl", role = "aut"),
person("Ines", "Wilms", email = "i.wilms@maastrichtuniversity.nl", role = "aut")
)
Calculates the desparsified lasso as originally introduced in van de Geer et al. (2014) <doi:10.1214/14-AOS1221>, and provides inference suitable for high-dimensional time series, based on the long run covariance estimator in Adamek et al. (2020) <arXiv:2007.10952>.
Robert Adamek [cre, aut],
Stephan Smeekes [aut],
Ines Wilms [aut]