MultiGrey (version 0.1.0)

multigreyforecast: 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)

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.

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.

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)