Package: ARIMAANN 0.1.0

Mrinmoy Ray

ARIMAANN: Time Series Forecasting using ARIMA-ANN Hybrid Model

Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model. The ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN) model for time series forecasting.For method details see Zhang, GP (2003) <doi:10.1016/S0925-2312(01)00702-0>.

Authors:Ramasubramanian V. [aut, ctb], Mrinmoy Ray [aut, cre]

ARIMAANN_0.1.0.tar.gz
ARIMAANN_0.1.0.tar.gz(r-4.7-any)ARIMAANN_0.1.0.tar.gz(r-4.6-any)
ARIMAANN_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ARIMAANN/json (API)

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

On CRAN:

Conda:

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

1.30 score 2 stars 1 scripts 267 downloads 1 exports 38 dependencies

Last updated from:19cb732d06. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK126
source / vignettesOK175
linux-release-x86_64OK127
wasm-releaseOK127

Exports:ARIMAANN

Dependencies:clicolorspacecpp11curlfarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrnlmennetquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDatetseriesTTRurcavctrsviridisLitewithrxtszoo