M-estimation is a widely used technique for robust statistical inference. In this paper, we study model selection and model averaging for M-estimation to simultaneously improve the coverage probability of confidence intervals of the parameters of interest and reduce the impact of heavy-tailed errors ...
The second step is to find suitable model weights for averaging. To minimize the prediction error, we estimate the model weights using a delete-one cross-validation procedure. Departing from the literature of model averaging that requires the weights always sum to one, an important improvement we...
estimation methods in situations with the number of variables much smaller than the sample size, this article concentrates on the additional difficulties and challenges when applying focused model selection for squared error loss with penalized estimation, for example, in a context of high-dimensional ...
Yulia Marchenko (StataCorp) 14 / 42 Bayesian model averaging Toy example BMA linear regression Estimation: Model enumeration (few predictors, fixed g ); 210 = 1,024 considered models. Default priors: Beta-binomial(1,1) for models and fixed g = 200. Little shrinkage: g /(1 + g ) = ...
The goal of this study was to compare the model-averaging approach with SSD estimation based on single statistical distributions (hereafter referred to as the single-distribution approach) to estimate HC5 values when toxicity data are available for a limited number of species. For this comparison,...
Hadley E, Rhea S, Jones K, Li L, Stoner M, Bobashev G. Enhancing the prediction of hospitalization from a COVID-19 agent-based model: a Bayesian method for model parameter estimation. PLoS One. 2022;17(3):e0264704. Article CAS PubMed PubMed Central Google Scholar Xiang HX, Fei J...
Section 2 introduces the VAR(∞) model and parameter estimation approach. Section 3 proposes the LsoMA criterion for VAR(∞) and Section 4 establishes its theoretical properties. Section 5 conducts simulation experiments. Section 6 applies the proposed method to a quarterly U.S. data set and a...
BMA postestimation — Postestimation tools for Bayesian model averaging Description Remarks and examples Also see Description The following Bayesian model averaging (BMA) postestimation commands are available after bmaregress: Command Description bmacoefsample posterior samples of regression coefficients bma...
Emission estimation model for flights. Contribute to google/travel-impact-model development by creating an account on GitHub.
and model averaging can play an important role in the QR model building process. There is a growing literature on model selection for QR models or more generally, -estimation. For example, Hurwich and Tsai (1990) develop a small sample criterion for the selection of LAD regression models; Mac...