Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted-average least squares (WALS) is a recent model-average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications
A model averaged estimator is composed of estimators, each obtained from a different model, that are...
This paper considers the problem of selection of weights for averaging across least squares estimate...
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the contex...
Model averaging has become a popular method of estimation, following increasing evidence that model ...
We consider inference for linear regression models estimated by weighted-average least squares (WALS...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
Parameter estimation under model uncertainty is a difficult and fundamental issue in econometrics. T...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
The method of model averaging has become an important tool to deal with model uncertainty, in parti...
The method of model averaging has become an important tool to deal with model uncertainty, for examp...
This paper derives the limiting distributions of least squares averaging estimators for linear regre...
A model averaged estimator is composed of estimators, each obtained from a different model, that are...
This paper considers the problem of selection of weights for averaging across least squares estimate...
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the contex...
Model averaging has become a popular method of estimation, following increasing evidence that model ...
We consider inference for linear regression models estimated by weighted-average least squares (WALS...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
Parameter estimation under model uncertainty is a difficult and fundamental issue in econometrics. T...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
In this article, we describe the estimation of linear regression models with uncertainty about the c...
The method of model averaging has become an important tool to deal with model uncertainty, in parti...
The method of model averaging has become an important tool to deal with model uncertainty, for examp...
This paper derives the limiting distributions of least squares averaging estimators for linear regre...
A model averaged estimator is composed of estimators, each obtained from a different model, that are...
This paper considers the problem of selection of weights for averaging across least squares estimate...
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the contex...
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