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JSRI 2008, 5(1): 95-121 Back to browse issues page
Functional Modeling of Iranian Precipitation Based on Temperature and Humidity
E. Hosseini-nasab *1, N. Kheirolah-zadeh, N. Tazikeh Miyandarreh
1- , m_hosseininasab@sbu.ac.ir
Abstract:   (2640 Views)

Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Modeling of Iranian precipitation based on temperature and humidity with continuous the essential nature of such phenomena that are continuous functions of time has not been done properly. The corresponding data are generally collected daily or monthly (discretely). However, if one treats those data as multivariate observations and analyzes by multivariate methods, it may cause some problems such as infinite number of solutions for normal equations in regression.

In regard to the fact that the original discrete data must be firstly converted to continuous functions, we usually use “basis function methods” for dimension reduction of the data due to its simplicity. In this article, problems arising form using multiple regression methods instead of applying functional regression approaches are discussed.

We have treated a real dataset that was collected from 102 Iranian weather stations in 2006. The dataset ... [To continue please click here]

Keywords: Functional data analysis, functional regression, smoothing, basis functions
Full-Text [PDF 1327 kb]   (1330 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/01/20 | Accepted: 2016/01/20 | Published: 2016/01/20
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Hosseini-nasab E, Kheirolah-zadeh N, Tazikeh Miyandarreh N. Functional Modeling of Iranian Precipitation Based on Temperature and Humidity . JSRI. 2008; 5 (1) :95-121
URL: http://jsri.srtc.ac.ir/article-1-124-en.html

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Volume 5, Issue 1 (9-2008) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران Journal of Statistical Research of Iran JSRI
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