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TSLSTM  

Long Short Term Memory (LSTM) Model for Time Series Forecasting
View on CRAN: Click here


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

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

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



Attach the package and use:
library("TSLSTM")
Maintained by
Dr. Ranjit Kumar Paul
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-13
Latest Update: 2022-01-13
Description:
The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network (RNN) based architecture that is widely used for time series forecasting. Min-Max transformation has been used for data preparation. Here, we have used one LSTM layer as a simple LSTM model and a Dense layer is used as the output layer. Then, compile the model using the loss function, optimizer and metrics. This package is based on Keras and TensorFlow modules and the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.
How to cite:
Dr. Ranjit Kumar Paul (2022). TSLSTM: Long Short Term Memory (LSTM) Model for Time Series Forecasting. R package version 0.1.0, https://cran.r-project.org/web/packages/TSLSTM. Accessed 10 Oct. 2026.
Previous versions and publish date:
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Complete documentation for TSLSTM
Functions, R codes and Examples using the TSLSTM R package
Some associated functions: ts.lstm . 
Some associated R codes: TSLSTM.R .  Full TSLSTM package functions and examples
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