作者：Kato, Kengo
作者单位：University of Tokyo
摘要：This paper aims at developing a quasi-Bayesian analysis of the nonparametric instrumental variables model, with a focus on the asymptotic properties of quasi-posterior distributions. In this paper, instead of assuming a distributional assumption on the data generating process, we consider a quasi-likelihood induced from the conditional moment restriction, and put priors on the function-valued parameter. We call the resulting posterior quasi-posterior, which corresponds to Gibbs posterior in th...
作者：Chatterjee, Sourav; Diaconis, Persi
作者单位：Stanford University
摘要：We introduce a method for the theoretical analysis of exponential random graph models. The method is based on a large-deviations approximation to the normalizing constant shown to be consistent using theory developed by Chatterjee and Varadhan [European J. Combin. 32 (2011) 1000-1017]. The theory explains a host of difficulties encountered by applied workers: many distinct models have essentially the same MLE, rendering the problems practically ill-posed. We give the first rigorous proofs of d...
作者：Zhao, Junlong; Leng, Chenlei; Li, Lexin; Wang, Hansheng
作者单位：Beihang University; University of Warwick; National University of Singapore; North Carolina State University; Peking University
摘要：Influence diagnosis is important since presence of influential observations could lead to distorted analysis and misleading interpretations. For high-dimensional data, it is particularly so, as the increased dimensionality and complexity may amplify both the chance of an observation being influential, and its potential impact on the analysis. In this article, we propose a novel high-dimensional influence measure for regressions with the number of predictors far exceeding the sample size. Our p...
