GM {GreyModel}

Grey Model Fitting

Description

The GM function fit GM (1, 1) model for time series data.

Usage

GM(data)

Arguments

data

Input univariate time series (ts) data.

Details

In situations where there are limited observations available for modelling, grey modelling may be employed (Hsu and Wang, 2007). Using the OLS approach, this function calculates the parameters (a and b) of the GM (1, 1) model. Additionally, this function returns the model's fitted values and different evaluation criteria.

Value

a

Grey model parameter

b

Grey model parameter

MAE_Grey

Mean Absolute Error (MAE) of fitted Grey model

MAPE_Grey

Mean Absolute Percentage Error (MAPE) of fitted Grey model

MSE_Grey

Mean Square Error (MSE) of fitted Grey model

RMSE_Grey

Root Mean Square Error (RMSE) of fitted Grey model

fitted

Fitted values of Grey model

References

Hsu, L. and Wang, C. (2007). Forecasting the output of integrated circuit industry using a grey model improved by the Bayesian analysis. Technological Forecasting and Social Change, 74, 843–853.

Mao, M. and Chirwa, E. C. (2006). Application of grey model GM(1, 1) to vehicle fatality risk estimation. Technological Forecasting and Social Change, 73, 588–605.

See Also

GM_test, fcast_grey

Examples

xt <- c(640,724,813,1145,1509,2122,1883,2413,2834,4235,7144,5269)
GM(xt)