Package: LTAR 0.1.0
LTAR: Tensor Forecasting Functions
A set of tools for forecasting the next step in a multidimensional setting using tensors. In the examples, a forecast is made of sea surface temperatures of a geographic grid (i.e. lat/long). Each observation is a matrix, the entries in the matrix and the sea surface temperature at a particular lattitude/longitude. Cates, J., Hoover, R. C., Caudle, K., Kopp, R., & Ozdemir, C. (2021) "Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting" in 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 461-466), IEEE <doi:10.1109/ICMLA52953.2021.00078>.
Authors:
LTAR_0.1.0.tar.gz
LTAR_0.1.0.zip(r-4.5)LTAR_0.1.0.zip(r-4.4)LTAR_0.1.0.zip(r-4.3)
LTAR_0.1.0.tgz(r-4.4-any)LTAR_0.1.0.tgz(r-4.3-any)
LTAR_0.1.0.tar.gz(r-4.5-noble)LTAR_0.1.0.tar.gz(r-4.4-noble)
LTAR_0.1.0.tgz(r-4.4-emscripten)LTAR_0.1.0.tgz(r-4.3-emscripten)
LTAR.pdf |LTAR.html✨
LTAR/json (API)
| # Install 'LTAR' in R: |
| install.packages('LTAR', repos = c('https://kylecaudle.r-universe.dev', 'https://cloud.r-project.org')) |
- tensor - Sea Surface Temperatures
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:7218520dd4. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 18 2024 |
| R-4.5-win | OK | Nov 18 2024 |
| R-4.5-linux | OK | Nov 18 2024 |
| R-4.4-win | OK | Nov 18 2024 |
| R-4.4-mac | OK | Nov 18 2024 |
| R-4.3-win | OK | Nov 18 2024 |
| R-4.3-mac | OK | Nov 18 2024 |
Dependencies:gsignallatticelmtestMASSMatrixmatrixcalcnlmepngpracmarasterRcpprTensorrTensor2sandwichspstrucchangeterraurcavarswavethreshzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Forecast error calculations | err |
| Tensor Autoregression (TAR) Model | LTAR |
| Forecast for a 3D Tensor Autoregression Model | LTARpred |
| Tensor Transformation | Ltrans |
| Sea Surface Temperatures | tensor |
