A Bernoulli autoregressive moving average model applied to rainfall occurrence. Issue 9 (21st October 2019)

• Record Type: Journal Article
• Authors: Angelo Milani, Eder; Hartmann, Marcelo; Andrade, Marinho G.; Ribeiro Diniz, Carlos Alberto
• Is Part Of: Communications in statistics. Volume 48:Issue 9(2019)
• Page Start: 2743
• Page End: 2756
• Publication Date: 2019-10-21
• Subjects: Bernoulli conditional distribution -- binary time series models -- GARMA models -- rain forecast; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2018.1468453
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: In this article, we propose a new model for binary time series involving an autoregressive moving average structure. The proposed model, which is an extension of the GARMA model, can be used for calculating the forecast probability of an occurrence of an event of interest in cases where these probabilities are dependent on previous observations in the near term. The proposed model is used to analyze a real dataset involving a series that contains only data 0 and 1, indicating the absence or presence of rain in a city located in the central region of São Paulo state, Brazil.