In model-assisted estimation, how are auxiliary variables incorporated? What assumptions are made when using auxiliary variables in estimation?

Nov 10, 2020 ... Title:Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration ... Abstract:Discrete structures play an important role in ... Nov 18, 2022 ... A simulation study: Improved ratio-in-regression type variance estimator based on dual use of auxiliary variable under simple random sampling. Aug 12, 2019 ... I want to iterate over then with an auxiliar variable, like i, because when some condition is met (like EC is different of RG), I want that this iteration go ... While TLA+ properties have a lot of flexibility, they also have limits. You can't “forget” a property, like say “P is true until Q is true, after while P can be ... The new auxiliary datasets contain data derived from the regular FARS/GES variables using NCSA analyti- cal data classifications. These classifications are ... We stipulate a new structural rule for adjusting auxiliary variables when strengthening preconditions and weakening postconditions. Courtesy of this new rule, ... Auxiliary variables are used in multiple imputation (MI) to reduce bias and increase efficiency. These variables may often themselves be incomplete. Mar 4, 2025 ... Holmes, C C; Held, L (2006). Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis, 1(1):145-168. This article, empirically, investigates to ascertain the importance of correlation level in the use of auxiliary variable in estimating the population parameter The U.S. Geological Survey's Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and ...