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stat.ME2026

A Total Statistical Error Framework for Comparing Census Data Collection Methods

Siu-MIng Tam, Anders Holmberg

Population censuses increasingly rely on imputation to assign usual-residence addresses for non-responding dwellings, yet no formal statistical framework has existed for comparing…

stat.ME2026

Bayesian Seasonal Adjustment for Survey Time Series

Siu-Ming Tam

Seasonal adjustment procedures used by national statistical offices -- X-11 and X-12-ARIMA -- treat each survey estimate as an exact observation, discarding the accompanying standa…

stat.ME2026

Dynamic Mini Max Design and Sequential HB Inference for Repeated Surveys

Siu-Ming Tam

TThis paper develops a Dynamic Mini-Max (DMM) framework for repeated surveys comprising a Dynamic Mini-Max Design and a Sequential Hierarchical Bayes Update (SHBU). The DMM jointly…

stat.ME2026

Post-Hoc Inference of Cross-Classified Statistics from Hierarchical Bayes Survey Weights

Siu-Ming Tam

Tam [2026] shows that combining Bethel multivariate allocation with Hierarchical Bayes (HB) small area models can substantially reduce survey sample sizes while maintaining domain-…

stat.ME2026

More with Less -- Bethel Allocation and Precision-Preserving Sample Size Reduction via Hierarchical Bayes Modelling

Siu-Ming Tam

Statistical offices face a familiar and intensifying dilemma: rising demand for detailed regional and domain-level estimates under budgets that are fixed or shrinking. National sta…

stat.ME2025

On linkage bias-correction for estimators using iterated bootstraps

Siu-Ming Tam, Min Wang, Alicia Rambaldi +1

By amalgamating data from disparate sources, the resulting integrated dataset becomes a valuable resource for statistical analysis. In probabilistic record linkage, the effectivene…