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

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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- , m.moradinazar@gmail.com
Abstract:   (20814 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]   (7145 Downloads)    
Type of Study: Review Article | Subject: General
Received: 2015/08/16 | Accepted: 2015/08/16 | Published: 2015/08/16

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by : Yektaweb