Package: EEMDlstm
Type: Package
Title: EEMD Based LSTM Model for Time Series Forecasting
Version: 0.1.0
Authors@R: 
  c(person(given = "Kapil",
         family = "Choudhary",
         role = c("aut", "cre"),
         email = "kapiliasri@gmail.com"),
  person(given = "Girish Kumar",
         family = "Jha",
         role =  c("aut", "ths", "ctb")),
  person(given = "Ronit",
         family = "Jaiswal",
         role = c( "ctb")),
  person(given = "Rajeev Ranjan ",
         family = "Kumar",
         role =  c( "ctb")))
Maintainer: Kapil Choudhary <kapiliasri@gmail.com>
Description: Forecasting univariate time series with ensemble empirical mode decomposition (EEMD) with long short-term memory (LSTM). For method details see Jaiswal, R. et al. (2022). <doi:10.1007/s00521-021-06621-3>. 
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Imports: keras, tensorflow, reticulate, tsutils, BiocGenerics, utils,
        graphics, magrittr,Rlibeemd, TSdeeplearning
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-09-24 01:11:19 UTC; kapil
Author: Kapil Choudhary [aut, cre],
  Girish Kumar Jha [aut, ths, ctb],
  Ronit Jaiswal [ctb],
  Rajeev Ranjan Kumar [ctb]
Repository: CRAN
Date/Publication: 2022-09-26 12:30:02 UTC
Built: R 4.1.2; ; 2022-09-27 11:37:49 UTC; unix
