Ensemble of networks has been proven to give better prediction result than a single network. Two commonly used way of determining the ensemble weights are simple average ensemble method and the generalized ensemble method. In the paper, we propose the weighted least square ensemble network. The major difference between this method and the other ensemble methods is that we do not assume that nei...

This work deals with the weighted excesses of players in cooperative games which are obtained by summing up all coalitions to they belong. We first show that resulting payoff vector is corresponding least square value lexicographically minimizing individual over preimputation set, and thus give an alternative characterization values. Second, we these results rise lower upper bounds for core vec...

We extend the results of De Luca et al. (2021) to inference for linear regression models based on weighted-average least squares (WALS), a frequentist model averaging approach with Bayesian flavor. We concentrate about single focus parameter, interpreted as causal effect policy or intervention, in presence potentially large number auxiliary parameters representing nuisance component model. In ...