Package: ProbReco
Type: Package
Title: Score Optimal Probabilistic Forecast Reconciliation
Version: 0.1.0.1
Authors@R: c(person(given = "Anastasios",
             family = "Panagiotelis",
             email = "anastasios.panagiotelis@sydney.edu.au",
             role = c("aut", "cre"),
             comment = c(ORCID = "0000-0001-8678-7294")))
Description: Training of reconciliation weights for probabilistic forecasts to optimise total energy (or variogram) score using Stochastic Gradient Descent with automatically differentiated gradients. See Panagiotelis, Gamakumara, Athanasopoulos and Hyndman, (2020) <https://www.monash.edu/business/ebs/research/publications/ebs/wp26-2020.pdf> for a description of the methods.
License: GPL-3
URL: https://github.com/anastasiospanagiotelis/ProbReco
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.2), purrr(>= 0.3.2), mvtnorm, Rdpack
Suggests: knitr, rmarkdown, fable, dplyr,tidyr, magrittr, stringi
LinkingTo: Rcpp, RcppEigen, StanHeaders (>= 2.19.1), BH
RdMacros: Rdpack
RoxygenNote: 7.1.1
LazyData: true
VignetteBuilder: knitr
Encoding: UTF-8
BugReports: https://github.com/anastasiospanagiotelis/ProbReco/issues
NeedsCompilation: yes
Packaged: 2020-09-24 05:24:56 UTC; anastasios
Author: Anastasios Panagiotelis [aut, cre]
    (<https://orcid.org/0000-0001-8678-7294>)
Maintainer: Anastasios Panagiotelis <anastasios.panagiotelis@sydney.edu.au>
Repository: CRAN
Date/Publication: 2020-09-24 08:10:06 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-09-25 10:51:01 UTC; unix
Archs: ProbReco.so.dSYM
