Modeling and Forecasting Monkeypox Cases Using Stochastic Models.

Qureshi, Moiz; Khan, Shahid; Bantan, Rashad A R; Daniyal, Muhammad; Elgarhy, Mohammed; Marzo, Roy Rillera; Lin, Yulan

Qureshi, Moiz; Khan, Shahid; Bantan, Rashad A R; Daniyal, Muhammad; Elgarhy, Mohammed; Marzo, Roy Rillera; Lin, Yulan.

Afiliación

Qureshi M; Department of Statistics, Shaheed Benazir Bhutto University, Nawabshah 67450, Pakistan.
Khan S; Department of Mathematics, National University of Modern Languages, Islamabad 44000, Pakistan.
Bantan RAR; Department of Marine Geology, Faculty of Marine Science, King AbdulAziz University, Jeddah 21551, Saudi Arabia.
Daniyal M; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.
Elgarhy M; The Higher Institute of Commercial Sciences, Al Mahalla Al Kubra 31951, Egypt.
Marzo RR; Department of Community Medicine, International Medical School, Management and Science University, Shah Alam 40100, Selangor, Malaysia.
Lin Y; Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Subang Jaya 47500, Selangor, Malaysia.

J Clin Med ; 11(21)2022 Nov 04.

Article en En | MEDLINE | ID: mdl-36362783

Palabras clave

ARIMA; MLP; monkeypox; pandemic; time series data analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Clin Med Año: 2022 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Suiza

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