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Bayesian Model Averaging for Linear Regression Models
 Journal of the American Statistical Association
, 1997
"... We consider the problem of accounting for model uncertainty in linear regression models. Conditioning on a single selected model ignores model uncertainty, and thus leads to the underestimation of uncertainty when making inferences about quantities of interest. A Bayesian solution to this problem in ..."
Abstract

Cited by 311 (15 self)
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We consider the problem of accounting for model uncertainty in linear regression models. Conditioning on a single selected model ignores model uncertainty, and thus leads to the underestimation of uncertainty when making inferences about quantities of interest. A Bayesian solution to this problem
Multivariate Linear Regression Model
"... The problem of air pollution is a frequently recurring situation and its management has social and economic considerable effects. Given the interaction of the numerous factors involved in the raising of the atmospheric pollution rates, it should be considered that the relation between the intensity ..."
Multiple Linear Regression Models
"... In this paper, we describe results to model lateral and longitudinal control behavior of drivers with simple linear multiple regression models. This approach fits into the Bayesian Programming (BP) approach (Bessière, 2008) because the linear multiple regression model suggests an action selection st ..."
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In this paper, we describe results to model lateral and longitudinal control behavior of drivers with simple linear multiple regression models. This approach fits into the Bayesian Programming (BP) approach (Bessière, 2008) because the linear multiple regression model suggests an action selection
(Non) Linear Regression Modeling
"... beschränkte einfache Recht ein, das ausgewählte Werk im Rahmen der unter ..."
(Non) Linear Regression Modeling
"... Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen ..."
CLT in functional linear regression models
 Probab. Theory Related Fields
, 2007
"... We propose in this work to derive a CLT in the functional linear regression model. The main difficulty is due to the fact that estimation of the functional parameter leads to a kind of illposed inverse problem. We consider estimators that belong to a large class of regularizing methods and we first ..."
Abstract

Cited by 9 (1 self)
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We propose in this work to derive a CLT in the functional linear regression model. The main difficulty is due to the fact that estimation of the functional parameter leads to a kind of illposed inverse problem. We consider estimators that belong to a large class of regularizing methods and we
Prognostics As Compared To Linear Regression Model
"... Abstract — Data driven prognostics employs many types of algorithms some are statics and other are dynamics. Dynamic complex engineering systems such as automobiles, aircraft, and spacecraft require dynamic data modeling which is very efficient to represent time series data. Dynamic models are compl ..."
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are complex and increase computational demands. In previous work performed by the author, linear regression model is provided to estimate the remaining useful life left of an aircraft turbofan engines and overcome the complexity of using dynamic models. It was simple and efficient but it had some drawbacks
Results 1  10
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2,802,160