Forecasting and evaluation of time series with multiple seasonal component
Seasonality is one of the components in time series analysis and this seasonal component may occur more than one time. Thus, modelling the seasonality by using one seasonal component is not enough and could produce less forecast accuracy. Autoregressive Integrated Moving Average (ARIMA) models is th...
Main Authors: | Zamri, Fatin Zafirah, Abd Rahman, Nur Haizum, Zulkafli, Hani Syahida |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Putra Malaysia
2021
|
Online Access: | http://psasir.upm.edu.my/id/eprint/97378/1/13922-2190-46665-1-10-20210619.pdf |
Similar Items
-
Activation functions performance in multilayer perceptron for time series forecasting
by: Nur Haizum, Abd Rahman, et al.
Published: (2024) -
Generalized Space-Time Autoregressive (GSTAR) for forecasting air pollutant index in Selangor
by: Nur Maisara Mohamed,, et al.
Published: (2023) -
Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor
by: Mohamed, Nur Maisara, et al.
Published: (2023) -
GARCH models and distributions comparison for nonlinear time series with volatilities
by: Nur Haizum, Abd Rahman, et al.
Published: (2023) -
Garch models and distributions comparison for nonlinear time series with volatilities
by: Abdul Rahman, Nur Haizum, et al.
Published: (2023)