Package: TSdeeplearning
Type: Package
Title: Deep Learning Model for Time Series Forecasting
Version: 1.0.1
Authors@R: 
  c(person(given = "Ronit",
         family = "Jaiswal",
         role = c("aut", "cre"),
         email = "ronitjaiswal2912@gmail.com"),
  person(given = "Girish Kumar",
         family = "Jha",
         role =  c("aut", "ths", "ctb")),
  person(given = "Rajeev Ranjan ",
         family = "Kumar",
         role =  c("aut", "ctb")),
  person(given = "Kapil",
         family = "Choudhary",
         role = c("aut", "ctb")))
Maintainer: Ronit Jaiswal <ronitjaiswal2912@gmail.com>
Description: Provides deep learning models for time series forecasting 
    using Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), 
    and Gated Recurrent Unit (GRU). These models capture temporal 
    dependencies and address vanishing gradient issues in sequential data. 
    The package enables efficient forecasting for univariate time series. 
    For methodological details see Jaiswal and co-authors (2022). 
    <doi:10.1007/s00521-021-06621-3>. 
Language: en-US
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
Imports: tensorflow, keras, reticulate, tsutils, BiocGenerics, utils,
        graphics, magrittr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2026-04-12 02:52:02 UTC; kapil
Author: Ronit Jaiswal [aut, cre],
  Girish Kumar Jha [aut, ths, ctb],
  Rajeev Ranjan Kumar [aut, ctb],
  Kapil Choudhary [aut, ctb]
Repository: CRAN
Date/Publication: 2026-04-13 07:20:15 UTC
Built: R 4.5.2; ; 2026-04-13 09:07:32 UTC; unix
