Package: TSLSTM 0.1.0

TSLSTM: Long Short Term Memory (LSTM) Model for Time Series Forecasting

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>.

Authors:Dr. Ranjit Kumar Paul [aut, cre], Dr. Md Yeasin [aut]

TSLSTM_0.1.0.tar.gz
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TSLSTM.pdf |TSLSTM.html
TSLSTM/json (API)

# Install 'TSLSTM' in R:
install.packages('TSLSTM', repos = c('https://ranjitstat.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 4 scripts 231 downloads 1 exports 80 dependencies

Last updated 3 years agofrom:276da206a1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 23 2024
R-4.5-winOKOct 23 2024
R-4.5-linuxOKOct 23 2024
R-4.4-winOKOct 23 2024
R-4.4-macOKOct 23 2024
R-4.3-winOKOct 23 2024
R-4.3-macOKOct 23 2024

Exports:ts.lstm

Dependencies:askpassbackportsbase64encclicolorspaceconfigcurlfansifarverforecastfracdiffgenericsggplot2gluegreyboxgtableherehttrisobandjsonlitekeraslabelinglatticelifecyclelmtestmagrittrMAPAMASSMatrixmgcvmimemunsellnlmenloptrnnetopensslpillarpkgconfigplotrixpngpracmaprocessxpsquadprogquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppTOMLreticulaterlangrprojrootrstudioapiscalessmoothstatmodsystensorflowtexregtfautographtfrunstibbletidyselecttimeDatetseriestsutilsTTRurcautf8vctrsviridisLitewhiskerwithrxtablextsyamlzeallotzoo