This article considers the problem of model averaging for regression models that can be nonlinear in their parameters and variables. We consider a (NMA) framework propose weight-choosing criterion, information criterion (NIC). show up to constant, NIC is an asymptotically unbiased estimator risk function under settings with some mild assumptions. also prove optimality convergence weights. Monte...

Logistic regression models are a popular and effective method to predict the probability of categorical response data. However, inference for these can become computationally prohibitive large datasets. Here we adapt ideas from symbolic data analysis summarize collection predictor variables into histogram form, perform on this summary dataset. We develop based composite likelihoods derive an ef...