arima_arnn: Hybrid ARIMA ARNN Forecasting Model

In hybridts: Hybrid Time Series Forecasting Using Error Remodeling Approach

Hybrid ARIMA ARNN Forecasting Model

Description

Hybrid ARIMA ARNN Forecasting Model

Usage

arima_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 = FALSE) for generating the prediction interval.
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

• Chakraborty, T., Chattopadhyay, S., & Ghosh, I. (2019). Forecasting dengue epidemics using a hybrid methodology. Physica A: Statistical Mechanics and its Applications, 527, 121266.

• Chakraborty, T., Ghosh, I., Mahajan, T., & Arora, T. (2022). Nowcasting of COVID-19 confirmed cases: Foundations, trends, and challenges. Modeling, Control and Drug Development for COVID-19 Outbreak Prevention, 1023-1064.

Examples

arima_arnn(y = datasets::lynx, n = 3)

hybridts documentation built on April 11, 2023, 5:59 p.m.