person("Jeroen", "Minderman", role = "ctb",
Suggests: knitr, rmarkdown, testthat, R.rsp
Author: A. Bradley Duthie [aut, cre] (<https://orcid.org/0000-0001-8343-4995>),
Nils Bunnefeld [ctb, fnd] (<https://orcid.org/0000-0002-1349-4463>),
Bram Van Moorter [ctb] (<https://orcid.org/0000-0002-3196-1993>)

person("Adrian", "Bach", role = c("ctb")),

person("Adrian", "Bach", role = c("aut")),
person("Jeroen", "Minderman", role = "aut",

person("Nils", "Bunnefeld", role = c("aut", "fnd"),
person("Ochoa", "Gabriela", role = "aut",
Nils Bunnefeld [aut, fnd] (<https://orcid.org/0000-0002-1349-4463>),

Nils Bunnefeld [aut, fnd] (<https://orcid.org/0000-0002-1349-4463>)

Title: Generalized Mass Spectrum Missing Peaks Abundance Imputation
Authors@R: person("Qian", "Li", email = "qian.li10000@gmail.com", role = c("aut", "cre"))
Description: Two-Step Lasso (TS-Lasso) and compound minimum methods to recover
the abundance of missing peaks in mass spectrum analysis. TS-Lasso is an
imputation method that handles various types of missing peaks simultaneously. This package
provides the procedure to generate missing peaks (or data) for simulation study,
as well as a tool to estimate and visualize the proportion of missing at random.
Imports: utils, glmnet, ggplot2, reshape2

Description: A collection of functions to perform statistical tests of the following methods: Detrended Fluctuation Analysis, RHODCCA coefficient,<doi:10.1103/PhysRevE.84.066118>, DMC coefficient, SILVA-FILHO et al. (2021) <doi:10.1016/j.physa.2020.125285>, Delta RHODCCA coefficient, Guedes et al. (2018) <doi:10.1016/j.physa.2018.02.148> and <doi:10.1016/j.dib.2018.03.080> , Delta DMCA coefficient and Delta DMC coefficient.
Maintainer: Everaldo Freitas Guedes <efgestatistico@gmail.com>
Imports: stats, base, DCCA, PerformanceAnalytics, nonlinearTseries,
Packaged: 2020-11-09 23:16:32 UTC; Everaldo Guedes
Author: Everaldo Freitas Guedes [aut, cre]
Gilney Figueira Zebende [aut] (<https://orcid.org/0000-0003-2420-9805>)

Imports: stats, DCCA, PerformanceAnalytics, nonlinearTseries,