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TSLSTMplus

1.0.6

Long-Short Term Memory for Time-Series Forecasting, Enhanced

0packages depend
2.4Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Jaime Pizarroso GonzaloFirst published 2023-11-217 releasesCRAN page ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 3.2 min · r-devel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
4
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
29%
Documented parameters
96%
Return-value docs
100%
References docs
29%

Downloads

2.4K
CRAN downloads in the past year
Rank #16,663 · ~7/day · ~203/mo
Daily download trend is not available in this view yet.
14730 days
63890 days
2.4K1 year
Compare downloads with other packages →
Also on124 r2u10 autocran14 c2d4u

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)
Depends (0)
none
Imports (4)
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Contributor, Maintainer
Authors (2)
Author, Contributor, Maintainer
Contributors (1)
Author, Contributor, Maintainer
Package Timeline

7 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.6Latest
    2025-02-03 · current release · diff ↗
  • 1.0.5
    2024-09-06 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 1.0.4
    2024-03-10 · diff ↗
  • 1.0.3
    2024-02-04 · diff ↗
  • 1.0.2
    2024-01-11 · diff ↗
  • 1.0.1
    2023-11-28 · diff ↗
  • 1.0.0
    2023-11-21
  • R
    R 4.3.0 released · 2023-04-21

Package metadata

First published
2023-11-21
Total releases
7 / 3 yrs
License
GPL-3 OSI
Download size
10 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("TSLSTMplus")
Pizarroso Gonzalo, J., & Muñoz San Roque, A. (2025). TSLSTMplus: Long-Short Term Memory for Time-Series Forecasting, Enhanced (Version 1.0.6) [Computer software]. https://doi.org/10.32614/CRAN.package.TSLSTMplus

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for TSLSTMplus version 1.0.6 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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