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:Kyle Caudle [aut, cre], Randy Hoover [ctb], Jackson Cates [ctb]

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LTAR.pdf |LTAR.html✨
LTAR/json (API)

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Last updated 1 years agofrom:7218520dd4. Checks:OK: 7. Indexed: yes.

Exports:errLTARLTARpredLtrans

Dependencies:gsignallatticelmtestMASSMatrixmatrixcalcnlmepngpracmarasterRcpprTensorrTensor2sandwichspstrucchangeterraurcavarswavethreshzoo