Time series analysis on precipitation with missing data using stochastic SARIMA

被引：0

作者：

Sharma, M. K. ^{[1
]}

Omer, Mohammed ^{[1
]}

Kiani, Sara ^{[2
]}

机构：

[1] Addis Ababa Univ, Coll Nat & Computat Sci, Dept Stat, Addis Ababa, Ethiopia

[2] Iran Univ, Tehran, Iran

来源：

MAUSAM | 2020年 / 71卷 / 04期

关键词：

Time series; Rainfall data; Missing data; ARIMA; SARIMA;

D O I：

暂无

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

This paper presents an application of the Box-Jenkins methodology for modeling the precipitation in Iran. Linear stochastic model known as multiplicative seasonal ARIMA was used to model the monthly precipitation data for 44 years. Missing data occurred in between for 34 months for some reason. To fill the gap a SARIMA model was fitted based on the first 180 available observations and the missing observations were substituted by the forecasts for the next 34 months. Then a SARIMA model was fitted for the full data. The result showed that the fitted model represent the full data well.

引用

页码：617 / 624

页数：8

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