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Regression Models

Jie Chen, A. K. Gupta

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Abstract

Regression analysis is an important statistical application employed in many disci-plines. Before the introduction of change point hypothesis into the regression study, a statistician faced some problems of being unable to establish a regression model for some observed data sets. 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 the data poorly explained by a regression model. Ever since the change point hypothesis has been 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 data sets after the change point has been located in the regression models. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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What this paper is about

Regression analysis is an important statistical application employed in many disci-plines. Before the introduction of change point hypothesis into the regression study, a statistician faced some problems of being unable to establish a regression model for some observed data sets. 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 the data poorly explained by a regression model. Ever since the change point hypothesis has been 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 data sets after the change point has been located in the regression models. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Available abstract

Regression analysis is an important statistical application employed in many disci-plines. Before the introduction of change point hypothesis into the regression study, a statistician faced some problems of being unable to establish a regression model for some observed data sets. 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 the data poorly explained by a regression model. Ever since the change point hypothesis has been 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 data sets after the change point has been located in the regression models. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Key concepts: Regression diagnostic, Regression analysis, Statistician, Regression, Segmented regression, Proper linear model, Cross-sectional regression, Nonparametric regression

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