arima_warima: Hybrid ARIMA WARIMA Forecasting Model

In hybridts: Hybrid Time Series Forecasting Using Error Remodeling Approach

Hybrid ARIMA WARIMA Forecasting Model

Description

Hybrid ARIMA WARIMA Forecasting Model

Usage

arima_warima(y, n, p = 5, q = 5, PI = FALSE, ret_fit = FALSE)

Arguments

y	A numeric vector or time series
n	An integer specifying the forecast horizon
p	An integer indicating the maximum order of AR process. Default is 5.
q	An integer indicating the maximum order of MA process. Default is 5.
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., & Ghosh, I. (2020). Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis. Chaos, Solitons & Fractals, 135, 109850.

• 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_warima(y = datasets::lynx, n = 3)

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