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LTAR  

Tensor Forecasting Functions
View on CRAN: Click here


Download and install LTAR package within the R console
Install from CRAN:
install.packages("LTAR")

Install from Github:
library("remotes")
install_github("cran/LTAR")

Install by package version:
library("remotes")
install_version("LTAR", "0.1.0")



Attach the package and use:
library("LTAR")
Maintained by
Kyle Caudle
[Scholar Profile | Author Map]
First Published: 2023-08-21
Latest Update: 2023-08-21
Description:
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 .
How to cite:
Kyle Caudle (2023). LTAR: Tensor Forecasting Functions. R package version 0.1.0, https://cran.r-project.org/web/packages/LTAR. Accessed 21 Feb. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited LTAR R package
View LTAR citation profile
Other R packages that LTAR depends, imports, suggests or enhances
Complete documentation for LTAR
Functions, R codes and Examples using the LTAR R package
Full LTAR package functions and examples
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