person("Daniel J.", "Schad", email = "schad@uni-potsdam.de", role = c("aut"), comment = c(ORCID = "0000-0003-2586-6823")))

Suggests: knitr, rmarkdown, tidyverse, jsonlite, writexl

Title: Sample Size Calculation of Various Study Designs
Description: Different sample size calculations with different study designs.
These techniques are explained by Chow (2007)

Title: Desirabiliy Function Optimization and Ranking
Description: S3 classes for multivariate optimization using the desirability function by Derringer and Suich (1980)
Packaged: Thu Apr 26 13:07:22 2007; kuhna03

Packaged: Mon Nov 26 22:44:32 2007; kuhna03

Packaged: Sun Jan 25 19:42:13 2009; kuhna03

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

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

Title: Function Optimization and Ranking via Desirability Functions

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

Author: Heike Trautmann, Detlef Steuer and Olaf Mersmann

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")
Description: 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>.

Title: Desparsified Lasso Inference for Time Series
Description: 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>. Also estimates high-dimensional local projections by the desparsified lasso, as described in Adamek et al. (2022) <arXiv:2209.03218>.
Imports: Rcpp, Rdpack, stats, parallelly