Volume 11, Number 1 (Vol 11, No 1 2015)                   irje 2015, 11(1): 94-102 | Back to browse issues page


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Hasanzadeh J, Najafi F, Moradinazar M. How to Choose an Appropriate Model for Time Series Data . irje. 2015; 11 (1) :94-102
URL: http://irje.tums.ac.ir/article-1-5353-en.html

1- Associate Professor, Department of Epidemiology, Shiraz university of Medical Sciences, Iran
2- Associate Professor, Department of Epidemiology, Research Center for Environmental Determinants of Health (RCEDH), Kermanshah University of Medical Sciences, Kermanshah, Iran
3- PhD candidate of epidemiology, Research Center for Environmental Determinants of Health (RCEDH), Kermanshah University of Medical Sciences, Kermanshah, Iran , m.moradinazar@gmail.com
Abstract:   (6771 Views)

The time series is a collection of observation data that are arranged according to time. The main purpose of setting up a time series is to predict future values. The first step in time series data is graphed. Using graphs can provide general information such as uptrend or downtrend, seasonal patterns, periodic presence, and outliers in time series graphs. After graphing the data, if a good forecast is required, stationary data can be used. Differencing or decomposition methods can be used to make the data stationary. Then, a correlogram can be used to identify the order moving average and autoregressive model. The parameters of the model are examined using T-test. If the parameters are significant and the residue is independence, the predicted values can be evaluated using the mean absolute percentage error.

Full-Text [PDF 1938 kb]   (2448 Downloads)    
Type of Study: Review Article | Subject: General
Received: 2015/08/16 | Accepted: 2015/08/16 | Published: 2015/08/16

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