Abstract:We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced...
Abstract: Respondent-Driven Sampling is type of link-tracing network sampling used to study hard-to-reach populations. Beginning with a convenience sample, each person sampled is given 2-3 uniquely identified coupons to distribute to other members of the...
Abstract: Corporations and political action committees (PACs) flood congressional elections with money. Understanding why they contribute is essential for determining how money in- fluences policy in Congress. To test theories of contributors’...
Abstract: Latent variable models provide a powerful tool for summarizing data through a set of hidden variables. These models are generally trained to maximize prediction accuracy, and modern latent variable models now do an excellent job of finding...
Abstract: Presidential, gubernatorial, and senatorial elections all require state-level polling, but even during presidential campaigns, state-level surveys remain sparse, erratically timed, and entirely neglected in uncompetitive states. Partly in...
Abstract: Achieving balance between experimental groups is a cornerstone of causal inference. Without balance any observed difference may be attributed to a difference other than the treatment alone. In controlled/clinical trials, where the experimenter...
