<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>Science and Education Publishing</publisher>
<journalTitle>Journal of Automation and Control</journalTitle>
<eissn>2372-3041</eissn>
<publicationDate>2015-12-15</publicationDate>
<volume>3</volume>
<issue>3</issue>
<startPage>118</startPage>
<endPage>121</endPage>
<doi>10.12691/automation-3-3-16</doi>
<publisherRecordId>AUTOMATION20153316</publisherRecordId>
<documentType>article</documentType>
<title language="eng">Regression Analysis and Seasonal Adjustment of Time Series</title>
<authors>
<author>
<name>Eva Ostertagová</name>
<email>eva.ostertagova@tuke.sk</email>
<affiliationId>1</affiliationId>
</author>
<author>
<name>Oskar Ostertag</name>
<affiliationId>2</affiliationId>
</author>

</authors>
<affiliationsList>
<affiliationName affiliationId="1">Department of Mathematics and Theoretical Informatics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Nemcovej 32, 042 00 Košice, Slovak Republic</affiliationName>
<affiliationName affiliationId="2">Department of Applied Mechanics and Mechatronics, Faculty of Mechanical Engineering, Technical University of Košice, Letná 9, 042 00 Košice, Slovak Republic</affiliationName>
</affiliationsList>
<abstract language="eng">The aim of this article is to demonstrate the dummy variables for estimation seasonal effects in a time series, to use them as inputs in a regression model for obtaining quality predictions. Model parameters were estimated using the least square method. After fitting, special tests to determine, if the model is satisfactory, were employed. The application data were analyzed using the MATLAB computer program that performs these calculations.</abstract>
<fullTextUrl format="pdf">http://pubs.sciepub.com/automation/3/3/16/automation-3-3-16.pdf</fullTextUrl>
<keywords language="eng"><keyword>seasonal time series</keyword>
<keyword>dummy variables</keyword>
<keyword>trigonometric regression functions</keyword>
<keyword>method of least squares</keyword>
<keyword>residual analysis</keyword>
</keywords>
</record>
</records>
