CRAN/E | ARMALSTM

ARMALSTM

Fitting of Hybrid ARMA-LSTM Models

Installation

About

The real-life time series data are hardly pure linear or nonlinear. Merging a linear time series model like the autoregressive moving average (ARMA) model with a nonlinear neural network model such as the Long Short-Term Memory (LSTM) model can be used as a hybrid model for more accurate modeling purposes. Both the autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models can be implemented. Details can be found in Box et al. (2015, ISBN: 978-1-118-67502-1) and Hochreiter and Schmidhuber (1997) doi:10.1162/neco.1997.9.8.1735.

Key Metrics

Version 0.1.0
Published 2024-02-28 51 days ago
Needs compilation? no
License GPL-3
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Maintainer

Maintainer

Debopam Rakshit

rakshitdebopam@yahoo.com

Authors

Debopam Rakshit

aut / cre

Ritwika Das

aut

Dwaipayan Bardhan

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Imports

rugarch
tseries
tensorflow
keras
reticulate