论文标题
在COVID-19中，自回归移动平均值和广义自动化移动平均值证实了印度尼西亚的案件
Autoregressive Moving Average and Generalized Autoregresive Moving Average in Covid-19 Confirmed Cases in Indonesia
论文作者
论文摘要
自回归移动平均值和广义自回归移动平均值通常用于统计建模中。该研究使用此方法，因为该方法使用上一个时期的数据对当前时期的数据进行建模。另外，该技术通常用于数据预测。所使用的熟悉数据是计数数据。计数数据是最常导致数据通常不传播的数据。因此，开发了时间序列建模，其中之一是通过算术系列。这项研究旨在从印度尼西亚的Covid 19阳性病例中获得最佳的建模结果。他们根据最小的Aikake信息标准值，从印度尼西亚的正面确认的Covid 19案例中获得最佳建模结果。
Autoregressive moving average and generalized autoregressive moving average are often used in statistical modeling. This study uses this method because the method uses data from the previous period to model the data for the current period. In addition, the technique is often used in data prediction. The familiar data used is count data. Count data is the data that most often cause data not to spread usually. Therefore, time series modeling, one of which is through arithmetic series, was developed. This study aims to obtain the best modeling results from positive confirmed cases of Covid 19 in Indonesia. They were getting the results from the best modeling for positive confirmed cases of Covid 19 in Indonesia based on the smallest Aikake information criterion value.
