首页> 外文期刊>Revista Brasileira de Meteorologia >PREVIS?O DA UMIDADE RELATIVA DO AR DE BRASíLIA POR MEIO DO MODELO BETA AUTORREGRESSIVO DE MéDIAS MóVEIS
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PREVIS?O DA UMIDADE RELATIVA DO AR DE BRASíLIA POR MEIO DO MODELO BETA AUTORREGRESSIVO DE MéDIAS MóVEIS

机译:通过BETA自回归模型预测巴西利亚空气的相对湿度

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摘要

Relative humidity (RH) monitoring is of great importance for the management of water resources, agricultural field, climatic studies, as well as for public health management. The objective of this paper is to analyze, model, and forecast the monthly RH at Brasília city, Distrito Federal, Brazil. RH is given in percentage terms, i.e., assume continuous values in the interval (0,1). In this situation the traditional time series models, like the ARIMA class, are not suitable. Thus, the use of beta autoregressive moving average models (βARMA) is required. This model proposed by Rocha and Cribari-Neto was developed for rates and proportions variable with beta distribution. For this study, the βARMA model was implemented in R language. Its application to RH data was adequate, capturing the behavior of the RH series and producing accurate predictions.
机译:相对湿度(RH)监测对于水资源,农业领域,气候研究以及公共卫生管理非常重要。本文的目的是分析,建模和预测巴西Distrito Federal,巴西利亚市的每月RH。 RH以百分比形式给出,即假设间隔(0,1)为连续值。在这种情况下,传统的时间序列模型(如ARIMA类)不合适。因此,需要使用β自回归移动平均模型(βARMA)。 Rocha和Cribari-Neto提出的该模型是针对比率和比例随β分布而变化的情况而开发的。对于本研究,以R语言实现了βARMA模型。它在RH数据上的应用是足够的,可以捕获RH系列的行为并产生准确的预测。

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