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作者：Fonseca, Thais C. O.; Ferreira, Marco A. R.
作者单位：Universidade Federal do Rio de Janeiro; Virginia Polytechnic Institute & State University
摘要：We propose a new class of dynamic multiscale models for Poisson spatiotemporal processes. Specifically, we use a multiscale spatial Poisson factorization to decompose the Poisson process at each time point into spatiotemporal multiscale coefficients. We then connect these spatiotemporal multiscale coefficients through time with a novel Dirichlet evolution. Further, we propose a simulation-based full Bayesian posterior analysis. In particular, we develop filtering equations for updating of info...
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作者：Hagemann, Andreas
作者单位：University of Michigan System; University of Michigan
摘要：In this article I develop a wild bootstrap procedure for cluster-robust inference in linear quantile regression models. I show that the bootstrap leads to asymptotically valid inference on the entire quantile regression process in a setting with a large number of small, heterogeneous clusters and provides consistent estimates of the asymptotic covariance function of that process. The proposed bootstrap procedure is easy to implement and performs well even when the number of clusters is much sm...
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作者：Robbins, Michael W.; Saunders, Jessica; Kilmer, Beau
作者单位：RAND Corporation; RAND Corporation
摘要：The synthetic control method is an increasingly popular tool for analysis of program efficacy. Here, it is applied to a neighborhood-specific crime intervention in Roanoke, VA, and several novel contributions are made to the synthetic control toolkit. We examine high-dimensional data at a granular level (the treated area has several cases, a large number of untreated comparison cases, and multiple outcome measures). Calibration is used to develop weights that exactly match the synthetic contro...
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作者：Wand, M. P.
作者单位：University of Technology Sydney; Queensland University of Technology (QUT)
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作者：Cabrera, Brenda Lopez; Schulz, Franziska
作者单位：Humboldt University of Berlin
摘要：Electricity load forecasts are an integral part of many decision-making processes in the electricity market. However, most literature on electricity load forecasting concentrates on deterministic forecasts, neglecting possibly important information about uncertainty. A more complete picture of future demand can be obtained by using distributional forecasts, allowing for more efficient decision-making. A predictive density can be fully characterized by tail measures such as quantiles and expect...
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作者：Rossell, David; Telesca, Donatello
作者单位：University of Warwick; University of California System; University of California Los Angeles
摘要：Jointly achieving parsimony and good predictive power in high dimensions is a main challenge in statistics. Nonlocal priors (NLPs) possess appealing properties for model choice, but their use for estimation has not been studied in detail. We show that for regular models NLP-based Bayesian model averaging (BMA) shrink spurious parameters either at fast polynomial or quasi-exponential rates as the sample size n increases, while nonspurious parameter estimates are not shrunk. We extend some resul...
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作者：Wand, M. P.
作者单位：University of Technology Sydney; Queensland University of Technology (QUT)
摘要：We show how the notion of message passing can be used to streamline the algebra and computer coding for fast approximate inference in large Bayesian semiparametric regression models. In particular, this approach is amenable to handling arbitrarily large models of particular types once a set of primitive operations is established. The approach is founded upon a message passing formulation of mean field variational Bayes that utilizes factor graph representations of statistical models. The under...
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作者：Johnson, Valen E.; Payne, Richard D.; Wang, Tianying; Asher, Alex; Mandal, Soutrik
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：Investigators from a large consortium of scientists recently performed a multi-year study in which they replicated 100 psychology experiments. Although statistically significant results were reported in 97% of the original studies, statistical significance was achieved in only 36% of the replicated studies. This article presents a reanalysis of these data based on a formal statistical model that accounts for publication bias by treating outcomes from unpublished studies as missing data, while ...
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作者：Konomi, Bledar A.; Karagiannis, Georgios; Lai, Kevin; Lin, Guang
作者单位：University System of Ohio; University of Cincinnati; Durham University; United States Department of Energy (DOE); Pacific Northwest National Laboratory; Purdue University System; Purdue University; Purdue University System; Purdue University; Purdue University in Indianapolis
摘要：In cases where field (or experimental) measurements are not available, computer models can model real physical or engineering systems to reproduce their outcomes. They are usually calibrated in light of experimental data to create a better representation of the real system. Statistical methods, based on Gaussian processes, for calibration and prediction have been especially important when the computer models are expensive and experimental data limited. In this article, we develop the Bayesian ...
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作者：Li, Jia; Todorov, Viktor; Tauchen, George
作者单位：Duke University; Northwestern University
摘要：We develop robust inference methods for studying linear dependence between the jumps of discretely observed processes at high frequency. Unlike classical linear regressions, jump regressions are determined by a small number of jumps occurring over a fixed time interval and the rest of the components of the processes around the jump times. The latter are the continuous martingale parts of the processes as well as observation noise. By sampling more frequently the role of these components, which...
