Package: TSSVM
Type: Package
Title: Time Series Forecasting using SVM Model
Version: 0.1.0
Authors@R: c(person(" Mrinmoy", "Ray", role = c("aut", "cre"),email = "mrinmoy4848@gmail.com"),
            person("Samir", "Barman", role = c("aut", "ctb")),
            person("Kanchan", "Sinha", role = c("aut", "ctb")),
           person("K. N.", "Singh", role = c("aut", "ctb")))                 
Depends: R (>= 2.3.1), e1071,forecast
Description: Implementation and forecasting univariate time series data using the Support Vector Machine model. Support Vector Machine is one of the prominent machine learning approach for non-linear time series forecasting. For method details see Kim, K. (2003) <doi:10.1016/S0925-2312(03)00372-2>.
Encoding: UTF-8
License: GPL-3
NeedsCompilation: no
Packaged: 2022-11-29 14:19:23 UTC; pc
Author: Mrinmoy Ray [aut, cre],
  Samir Barman [aut, ctb],
  Kanchan Sinha [aut, ctb],
  K. N. Singh [aut, ctb]
Maintainer: Mrinmoy Ray <mrinmoy4848@gmail.com>
Repository: CRAN
Date/Publication: 2022-12-02 08:10:02 UTC
Built: R 4.6.0; ; 2026-04-26 15:30:21 UTC; unix
