| theta_arnn {hybridts} | R Documentation |
Hybrid Theta ARNN Forecasting Model
Description
Hybrid Theta ARNN Forecasting Model
Usage
theta_arnn(y, n, PI = FALSE, ret_fit = FALSE)
Arguments
y |
A numeric vector or time series |
n |
An integer specifying the forecast horizon |
PI |
A logical flag (default = |
ret_fit |
A logical flag specifying that the fitted values of the model on the training set should be returned if true, otherwise, false (default) |
Value
The forecast of the time series of size n is generated along with the optional
output of fitted values (ret_fit = TRUE) and confidence interval (PI = TRUE) for the forecast.
References
Bhattacharyya, A., Chakraborty, T., & Rai, S. N. (2022). Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model. Nonlinear Dynamics, 1-16.
Bhattacharyya, A., Chattopadhyay, S., Pattnaik, M., & Chakraborty, T. (2021, July). Theta Autoregressive Neural Network: A Hybrid Time Series Model for Pandemic Forecasting. In 2021 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
Examples
theta_arnn(y = datasets::lynx, n = 3)