multigreyforecast {MultiGrey} | R Documentation |
Forecast the GM (1, 1) model for multivariate time series data
Description
The multigreyforecast function computes the h-step ahead forecast values for each of the variables in the multivariate time series data.
Usage
multigreyforecast(data, h)
Arguments
data |
Input multivariate time series data. |
h |
The forecast horizon. |
Details
This function returns the h-step ahead forecasted values of the fitted GM (1, 1) model for each of the variables in the multivariate time series data.
Value
A h-step ahead forecast values
forecast |
h-step ahead forecast values corresponding to each of the variables in the multivariate time series data. |
References
Akay, D. and Atak, M. (2007). Grey prediction with rolling mechanism for electricity demand forecasting of Turkey. Energy, 32(9), 1670-1675.<DOI:10.1016/j.energy.2006.11.014>
Deng, J. (1989). Introduction to grey system theory. The Journal of Grey System, 1(1), 1-24.
Hsu, L.C. and Wang, C.H. (2007). Forecasting the output of integrated circuit industry using a grey model improved by Bayesian analysis. Technological Forecasting and Social Change, 74(6), 843-853.<DOI:10.1016/j.techfore.2006.02.005>
Examples
# Example data
xt <- c(640, 684, 713, 745, 809, 811, 883, 893, 904, 935, 1044, 1069)
yt <- c(50, 64, 93, 113, 131, 152, 164, 201, 224, 268, 286, 290)
zt <- c(550,504,493,413,431,352,364,301,294,268,286,230)
data <- cbind(xt, yt, zt)
# Apply the multigreyfit function
multigreyforecast(data, h=3)