A Study of Time Series Model for Predicting Jute Yarn Demand: Case Study

Table 6

Summary of all forecasting methods and error calculations.

Forecasting method	MAPE	MAD	MSD
Multiplicative decomposition model with trend and seasonality	8.35	67.66	7573.78
Additive decomposition model with trend and seasonality	8.16	65.93	7467.41
Moving average	14.2	128.9	33243.4
Single exponential smoothing	6.5	53.6	15457
Holt’s method	13.2	110.6	27050.4
Trend analysis	15.39	134.16	32031.66
Winters multiplicative model	5.38	43.92	5089.33
Winters additive model	5.06	40.58	4705.68