Package: TSLSTMplus 1.0.6
Jaime Pizarroso Gonzalo
TSLSTMplus: Long-Short Term Memory for Time-Series Forecasting, Enhanced
The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network (RNN) based architecture that is widely used for time series forecasting. Customizable configurations for the model are allowed, improving the capabilities and usability of this model compared to other packages. 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:
TSLSTMplus_1.0.6.tar.gz
TSLSTMplus_1.0.6.tar.gz(r-4.5-noble)TSLSTMplus_1.0.6.tar.gz(r-4.4-noble)
TSLSTMplus_1.0.6.tgz(r-4.4-emscripten)TSLSTMplus_1.0.6.tgz(r-4.3-emscripten)
TSLSTMplus.pdf |TSLSTMplus.html✨
TSLSTMplus/json (API)
| # Install 'TSLSTMplus' in R: |
| install.packages('TSLSTMplus', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 months agofrom:cd8a7bcdb0. Checks:3 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 05 2025 |
| R-4.5-linux | OK | Mar 05 2025 |
| R-4.4-linux | OK | Mar 05 2025 |
Exports:lagmatrixLSTMModelminmax_scalets.lstmts.prepare.data
Dependencies:abindbackportsbase64enccliconfiggenericsglueherejsonlitekeraslatticelifecyclemagrittrMatrixpngprocessxpsR6rappdirsRcppRcppTOMLreticulaterlangrprojrootrstudioapitensorflowtfautographtfrunstidyselectvctrswhiskerwithryamlzeallot
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create lead/lags of a variable | lagmatrix |
| LSTMModel class | LSTMModel |
| Min-Max Scaling of a Matrix | minmax_scale |
| Predict using a Trained LSTM Model | predict.LSTMModel |
| Summary of a Trained LSTM Model | summary.LSTMModel |
| Long Short Term Memory (LSTM) Model for Time Series Forecasting | ts.lstm |
| Prepare data for Long Short Term Memory (LSTM) Model for Time Series Forecasting | ts.prepare.data |
