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 exports 0.36 score 46 dependencies 1 mentions 285 downloads

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

TargetResultDate
Doc / VignettesOKSep 09 2024
R-4.5-winOKSep 09 2024
R-4.5-linuxOKSep 09 2024
R-4.4-winOKSep 09 2024
R-4.4-macOKSep 09 2024
R-4.3-winOKSep 09 2024
R-4.3-macOKSep 09 2024

Exports:Auto.TSANN

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtablegtoolsisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo