The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian … WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized … linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification …

We investigate the asymptotic behavior of the WALS estimator, a model-averaging estimator with attractive finite …-sample and computational properties. WALS is closely related to the normal location model, and hence much of the paper concerns … a standard asymptotic setup with fixed parameters. We show that, under suitable conditions on the prior, the WALS …

We investigate the asymptotic behavior of the WALS estimator, a model-averaging estimator with attractive finite …-sample and computational properties. WALS is closely related to the normal location model, and hence much of the paper concerns … a standard asymptotic setup with fixed parameters. We show that, under suitable conditions on the prior, the WALS …

-average least squares (WALS), a method that has not previously been applied in this context. …

-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to …

-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to …

-known BMA and the recently developed WALS. Both methods propose to combine frequentist estimators using Bayesian weights. We …

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian … WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized … linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification …