Package: TSANN 0.1.0

TSANN: Time Series Artificial Neural Network

The best ANN structure for time series data analysis is a demanding need in the present era. This package will find the best-fitted ANN model based on forecasting accuracy. The optimum size of the hidden layers was also determined after determining the number of lags to be included. This package has been developed using the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.

Authors:Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Dipro Sinha [aut]

TSANN_0.1.0.tar.gz
TSANN_0.1.0.zip(r-4.5)TSANN_0.1.0.zip(r-4.4)TSANN_0.1.0.zip(r-4.3)
TSANN_0.1.0.tgz(r-4.4-any)TSANN_0.1.0.tgz(r-4.3-any)
TSANN_0.1.0.tar.gz(r-4.5-noble)TSANN_0.1.0.tar.gz(r-4.4-noble)
TSANN_0.1.0.tgz(r-4.4-emscripten)TSANN_0.1.0.tgz(r-4.3-emscripten)
TSANN.pdf |TSANN.html
TSANN/json (API)

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

Peer review:

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 215 downloads 1 mentions 1 exports 46 dependencies

Last updated 3 years agofrom:4b20978c3a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-winOKNov 08 2024
R-4.5-linuxOKNov 08 2024
R-4.4-winOKNov 08 2024
R-4.4-macOKNov 08 2024
R-4.3-winOKNov 08 2024
R-4.3-macOKNov 08 2024

Exports:Auto.TSANN

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtablegtoolsisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo