Seasonal time series model comparison for nonstationary passenger flight data

Moore, Theresa.; Youngstown State University. Dept. of Mathematics.

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dc.contributor.author	Moore, Theresa.	en_US
dc.contributor.author	Youngstown State University. Dept. of Mathematics.	en_US
dc.date.accessioned	2011-01-31T14:16:29Z
dc.date.accessioned	2019-09-08T02:35:55Z
dc.date.available	2011-01-31T14:16:29Z
dc.date.available	2019-09-08T02:35:55Z
dc.date.created	2007	en_US
dc.date.issued	2007	en_US
dc.identifier.other	b20249275	en_US
dc.identifier.uri	http://rave.ohiolink.edu/etdc/view?acc_num=ysu1197565064	en_US
dc.identifier.uri	http://jupiter.ysu.edu/record=b2024927	en_US
dc.identifier.uri	http://hdl.handle.net/1989/6080
dc.description	xi, 188 leaves : ill. ; 29 cm.	en_US
dc.description	Thesis (M.S.)--Youngstown State University, 2007.	en_US
dc.description	Includes bibliographical references (leaves 171).	en_US
dc.description.abstract	The objective of this paper is to analyze the number of passengers flying a sample of three airlines before and after 9/11 to discover whether there has been a recovery. The three airlines were modeled using simple linear regression and time series analysis. Dummy variables and trigonometric functions were used to mimic the seasonal variation and additive decomposition was used to remove the seasonal component and model the trend. The additive decomposition quadratic models were deemed the best fits. From the quadratic models is concluded that the three airlines chosen for this paper have recovered from the effects of 9/11.	en_US
dc.description.statementofresponsibility	by Theresa Moore.	en_US
dc.language.iso	en_US	en_US
dc.relation.ispartofseries	Master's Theses no. 0976	en_US
dc.subject.classification	Master's Theses no. 0976	en_US
dc.subject.lcsh	Air travel--United States.	en_US
dc.subject.lcsh	September 11 Terrorist Attacks, 2001.	en_US
dc.title	Seasonal time series model comparison for nonstationary passenger flight data	en_US
dc.type	Thesis	en_US

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