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stlTDNN  

STL Decomposition and TDNN Hybrid Time Series Forecasting
View on CRAN: Click here


Download and install stlTDNN package within the R console
Install from CRAN:
install.packages("stlTDNN")

Install from Github:
library("remotes")
install_github("cran/stlTDNN")

Install by package version:
library("remotes")
install_version("stlTDNN", "0.1.0")



Attach the package and use:
library("stlTDNN")
Maintained by
Girish Kumar Jha
[Scholar Profile | Author Map]
First Published: 2021-02-24
Latest Update: 2021-02-24
Description:
Implementation of hybrid STL decomposition based time delay neural network model for univariate time series forecasting. For method details see Jha G K, Sinha, K (2014). <doi:10.1007/s00521-012-1264-z>, Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.
How to cite:
Girish Kumar Jha (2021). stlTDNN: STL Decomposition and TDNN Hybrid Time Series Forecasting. R package version 0.1.0, https://cran.r-project.org/web/packages/stlTDNN. Accessed 05 Apr. 2025.
Previous versions and publish date:
No previous versions
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View stlTDNN citation profile
Other R packages that stlTDNN depends, imports, suggests or enhances
Complete documentation for stlTDNN
Functions, R codes and Examples using the stlTDNN R package
Some associated functions: Data_potato . STLTDNN . 
Some associated R codes: STLTDNN.R .  Full stlTDNN package functions and examples
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