In ecology, the true causal structure for a given problem is often not known, and several
plausible models and thus model predictions exist. It has been claimed that using weighted …

This paper considers the model averaging prediction in a quasi-likelihood framework that
allows for parameter uncertainty and model misspecification. We propose an averaging …

This paper considers the problem of selection of weights for averaging across least squares
estimates obtained from a set of models. Existing model average methods are based on …

In applications, the traditional estimation procedure generally begins with model selection.
Once a specific model is selected, subsequent estimation is conducted under the selected …

This paper is in response to a recent paper by Hansen (2007) who proposed an optimal
model average estimator with weights selected by minimizing a Mallows criterion. The main …

This article focuses on conducting global testing for association between a binary trait and a
set of rare variants (RVs), although its application can be much broader to other types of …

Considering model averaging estimation in generalized linear models, we propose a weight
choice criterion based on the Kullback–Leibler (KL) loss with a penalty term. This criterion is …

There has been increasing interest recently in model averaging within the frequentist
paradigm. The main benefit of model averaging over model selection is that it incorporates …

The past decade witnessed a literature on model averaging by frequentist methods. For the
most part, the asymptotic optimality of various existing frequentist model averaging …

This paper derives the limiting distributions of least squares averaging estimators for linear
regression models in a local asymptotic framework. We show that the averaging estimators …