Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)

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Model Identification and Derivation for Double Seasonal Integrated Moving Average (DSARIMA) Model

Authors
Puteri Aiman Syahirah Rosman1, *, Nur Haizum Abd Rahman1
1Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia (UPM), 43400, Serdang, Selangor, Malaysia
*Corresponding author. Email: GS58462@student.upm.edu.my
Corresponding Author
Puteri Aiman Syahirah Rosman
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-014-5_14How to use a DOI?
Keywords
DSARIMA; identification; additive; multiplicative; subset
Abstract

Double Seasonal Autoregressive Integrated Moving Average (DSARIMA) model is an extension of the single SARIMA that is incorporated in modelling data with two seasonality. Model identification, parameter estimation and diagnostic checking are the steps in the modelling. However, the model identification is the most crucial stage as it provides the information used in the next step. Thus, this study extended the derivation of the model identification for DSARIMA in all three models which are additive, multiplicative and subset. The daily and weekly seasonality which can be indicated by 24 and 128 were used in this study with the derivation involving correlation and covariance from the general form of both seasonal and non-seasonal parts. The derivation results were shown for ARIMA (0, 0, 1) (0, 0, 1)24(0, 0, 1)168, ARIMA (0, 0, [1, 24, 25, 168, 169, 192, 193]) and ARIMA (0, 0, [1, 24, 168]) for multiplicative, subset and additive models, respectively. In conclusion, this study gives a valuable insight into the model identification step in DSARIMA models.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
Series
Advances in Computer Science Research
Publication Date
12 December 2022
ISBN
10.2991/978-94-6463-014-5_14
ISSN
2352-538X
DOI
10.2991/978-94-6463-014-5_14How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Puteri Aiman Syahirah Rosman
AU  - Nur Haizum Abd Rahman
PY  - 2022
DA  - 2022/12/12
TI  - Model Identification and Derivation for Double Seasonal Integrated Moving Average (DSARIMA) Model
BT  - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
PB  - Atlantis Press
SP  - 141
EP  - 149
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-014-5_14
DO  - 10.2991/978-94-6463-014-5_14
ID  - Rosman2022
ER  -