Package: staRdom
Type: Package
Title: PARAFAC Analysis of EEMs from DOM
Version: 1.1.25
Date: 2022-03-10
Authors@R: c(person("Matthias", "Pucher", email = "matthias.pucher@boku.ac.at",
                  role = c("aut", "cre")),
                  person("Daniel", "Graeber", email = "daniel.graeber@ufz.de",
                  role = c("aut", "ctb")),
                  person("Stefan", "Preiner", email = "stefan.preiner@boku.ac.at",
                  role = c("ctb")),
                  person("Renata", "Pinto", email = "renatamspinto@sapo.pt",
                  role = c("ctb")))
Depends: R (>= 4.0), ggplot2 (>= 3.3.5), eemR (>= 1.0.1), parallel (>=
        4.0)
Description: This is a user-friendly way to run a parallel factor (PARAFAC) analysis (Harshman, 1971) <doi:10.1121/1.1977523> on excitation emission matrix (EEM) data from dissolved organic matter (DOM) samples (Murphy et al., 2013) <doi:10.1039/c3ay41160e>. The analysis includes profound methods for model validation. Some additional functions allow the calculation of absorbance slope parameters and create beautiful plots.
License: AGPL
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 1.0.8), tidyr (>= 1.2.0), stringr (>= 1.4.0), pracma
        (>= 2.3.3), zoo (>= 1.8-9), tibble (>= 3.1.6), multiway (>=
        1.0-6), GGally (>= 2.1.2), graphics (>= 4.0), doParallel (>=
        1.0.16), drc (>= 3.0-1), foreach (>= 1.5.1), data.table (>=
        1.14.2), matrixStats (>= 0.61.0), MBA(>= 0.0-9), cdom(>=
        0.1.0), R.matlab(>= 3.6.2), readr(>= 2.1.2), gtools(>= 3.9),
        viridisLite(>= 0.4)
Suggests: plotly, xlsx, knitr, kableExtra, askpass(>= 1.1), httr(>=
        1.4.2), rmarkdown
RoxygenNote: 7.1.2
VignetteBuilder: knitr
URL: https://cran.r-project.org/package=staRdom
BugReports: https://github.com/MatthiasPucher/staRdom/issues
NeedsCompilation: no
Packaged: 2022-03-10 09:45:44 UTC; maetz
Author: Matthias Pucher [aut, cre],
  Daniel Graeber [aut, ctb],
  Stefan Preiner [ctb],
  Renata Pinto [ctb]
Maintainer: Matthias Pucher <matthias.pucher@boku.ac.at>
Repository: CRAN
Date/Publication: 2022-03-21 15:50:02 UTC
Built: R 4.1.3; ; 2023-04-17 20:49:26 UTC; windows
