Regression Models

Jie Chen () and Arjun K. Gupta ()
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Jie Chen: University of Missouri-Kansas City, Department of Mathematics and Statistics
Arjun K. Gupta: Bowling Green State University, Department of Mathematics and Statistics

Chapter Chapter 4 in Parametric Statistical Change Point Analysis, 2012, pp 139-154 from Springer

Abstract: Abstract Regression analysis is an important statistical application employed in many disciplines. Before the introduction of a change point hypothesis into the regression study, the statistician faced problems of being unable to establish a regression model for some observed datasets. If the data structure has changed after a certain point of time, then using one regression model to study the data obviously leaves the data unfitted or leaves them poorly explained by a regression model. Ever since the change point hypothesis was introduced into statistical analyses, the study of switching regression models has taken place in regression analysis. This made some previously poorly fitted regression models better fitted to some datasets after the change point was been located in the regression models.

Keywords: Regression Model; Change Point; Linear Regression Model; Multiple Linear Regression Model; Posterior Density (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-8176-4801-5_4

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DOI: 10.1007/978-0-8176-4801-5_4

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