LTARpred {LTAR} | R Documentation |
Using a historical 3D tensor, the LTARpred function will forecast h steps into the future.
LTARpred(p, tnsr, h, type = c("const", "trend", "both", "none"), season = NULL)
p |
: Number of time series lags |
tnsr |
: A 3D tensor |
h |
: Number of steps to forecast |
type |
Type of deterministic regressors to include. |
season |
: Inclusion of centered seasonal dummy variables (integer value of frequency). |
A Tensor-class object which contains the h step forecasts.
Kyle Caudle
Randy Hoover
Jackson Cates
Cates, J., Hoover, R. C., Caudle, K., Kopp, R., & Ozdemir, C. (2021, December). 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.
require(rTensor)
data(tensor)
tnsr <- as.tensor(tensor)
result <- LTARpred(p=5,tnsr,h=2,type="trend",season=12)