Package: stlARIMA 0.1.0

stlARIMA: STL Decomposition and ARIMA Hybrid Forecasting Model

Univariate time series forecasting with STL decomposition based auto regressive integrated moving average (ARIMA) hybrid model. For method details see Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.

Authors:Ronit Jaiswal [aut, cre], Girish Kumar Jha [aut, ctb], Rajeev Ranjan Kumar [ctb], Kapil Choudhary [ctb]

stlARIMA_0.1.0.tar.gz
stlARIMA_0.1.0.zip(r-4.7-any)stlARIMA_0.1.0.zip(r-4.6-any)stlARIMA_0.1.0.zip(r-4.5-any)
stlARIMA_0.1.0.tgz(r-4.6-any)stlARIMA_0.1.0.tgz(r-4.5-any)
stlARIMA_0.1.0.tar.gz(r-4.7-any)stlARIMA_0.1.0.tar.gz(r-4.6-any)
stlARIMA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
stlARIMA/json (API)

# Install 'stlARIMA' in R:

install.packages('stlARIMA', repos = c('https://ronit10976.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Data_potato - Normalized Monthly Average Potato Price of India

On CRAN:

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

1.00 score 254 downloads 1 exports 31 dependencies

Last updated from:a7a5f03b02. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	150
source / vignettes	OK	181
linux-release	OK	125
macos-release	OK	158
macos-oldrel	OK	198
windows-devel	OK	86
windows-release	OK	82
windows-oldrel	OK	84
wasm-release	OK	121