R Observatory: Metrics for GARCHInfoLSTM version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

GARCHInfoLSTM

0.1.0Package record

GARCH-Informed LSTM Model for Volatility Forecasting

0packages depend

471downloads / year

0.0%test coverage

13/13flavors OK

Overview

About

Maintained by Ranjit Kumar PaulCRAN page ↗

The proposed Generalized Autoregressive Conditional Heteroskedasticity (GARCH)-informed Long Short-Term Memory (LSTM) model follows the concept of physics-informed machine learning (PIML) by integrating established econometric knowledge of price volatility into a data-driven forecasting framework. In the model, conditional volatility estimated from the GARCH process is incorporated as an additional explanatory signal or volatility-based weighting component within the LSTM architecture. This enables the LSTM to learn nonlinear temporal dependencies while remaining informed by the underlying characteristics of agricultural price series, including volatility clustering, heteroscedasticity and market uncertainty. The optimized weighting parameter, lambda, controls the contribution of the GARCH-derived volatility information to the final prediction. Thus, the model combines the statistical interpretability of GARCH with the nonlinear learning capability of LSTM, producing a hybrid PIML framework that is more responsive to both normal price movements and periods of extreme market volatility. The methodology is motivated by hybrid forecasting framework proposed by Yeasin and Paul (2024) doi:10.1007/s11227-023-05542-3.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("GARCHInfoLSTM", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-garchinfolstm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-GARCHInfoLSTM

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-GARCHInfoLSTM

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 57 s · r-oldrel-windows-x86_64

Status changes

OK13 OKNow
OK5 OK2026-09-22

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 340 wordsVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 5
Examples that run: 0%4 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 80%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

How these are measured

Downloads

471

CRAN downloads in the past year

Rank #24,778 · ~1/day · ~39/mo

Releases R versions

Daily download trend is not available in this view yet.

37530 days

47190 days

4711 year

Compare downloads with other packages →

Also on5 r2u

How downloads are counted

Dependencies

Declared dependencies

5 external dependencies (excludes base and recommended)

Installing GARCHInfoLSTM adds 58 packages (34 with compiled code, 34 MB of source tarballs). Heaviest: ggplot2 6.0 MB, mclust 2.7 MB, rugarch 2.6 MB.

Depends (0)

none

Imports (7)

torch rugarch ggplot2 cli corostatsutils

LinkingTo (0)

none

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (4)

Ranjit Kumar Paul

Author, Maintainer since 0.1.0 (2026)

Pushkar Bora

Author

Manojit Mandal

Author

Md Yeasin

Author

Releases (1)

0.1.0Latest
record
2026-09-21 · current release
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-09-21
Total releases: 1 / 1 yrs
License: MIT + file LICENSE OSI
Download size: 22 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GARCHInfoLSTM")

Format

Paul, R. K., Bora, P., Mandal, M., & Yeasin, M. (2026). GARCHInfoLSTM: GARCH-Informed LSTM Model for Volatility Forecasting (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.GARCHInfoLSTM

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

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

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GARCHInfoLSTM version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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