SARIMA MODELS WITH MULTIPLE SEASONALITY

التفاصيل البيبلوغرافية
العنوان: SARIMA MODELS WITH MULTIPLE SEASONALITY
المؤلفون: Luisa Bisaglia, Francesco Lisi
المساهمون: P. Coretto, G. Giordano, M. La Rocca, M.L. Parrella, C. Rampichini, Bisaglia, Luisa, Lisi, Francesco
بيانات النشر: Pearson Education Resources, Italia
سنة النشر: 2023
المجموعة: Padua Research Archive (IRIS - Università degli Studi di Padova)
مصطلحات موضوعية: Time series, Multiple seasonality, mSARIMA, seasonal-trend decom- position models
الوصف: SARIMA models and exponential smoothing methods are classical ap- proaches to account seasonal dynamics. However, they tipically allow to model just one periodic component, while many empirical time series data show multiple season- ality, possibly interlacing toghether. To face this case, different decomposition models have been proposed in literature, while SARIMA models have been quite neglected. To fill the gap, in this work we suggest a suitable specification of the SARIMA model, called mSARIMA, able to account multiple seasonality. To study its performance, we compare it with two popular seasonal-trend decomposition approaches, namely the TBATS and MSTL models. A simulation exercise shows that mSARIMA models are more effective in describing the the different seasonal components.
نوع الوثيقة: conference object
وصف الملف: ELETTRONICO
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/isbn/9788891935632; 14th Scientific Meeting of the Classification and Data Analysis Group; firstpage:358; lastpage:361; numberofpages:4; alleditors:P. Coretto, G. Giordano, M. La Rocca, M.L. Parrella, C. Rampichini; https://hdl.handle.net/11577/3509092Test; https://it.pearson.com/content/dam/region-core/italy/pearson-italy/pdf/Docenti/UniversitATest̃ /CLADAG-2023.pdf
الإتاحة: https://hdl.handle.net/11577/3509092Test
https://it.pearson.com/content/dam/region-core/italy/pearson-italy/pdf/Docenti/UniversitATest̃ /CLADAG-2023.pdf
رقم الانضمام: edsbas.111ABDE3
قاعدة البيانات: BASE