2024/03/27 by Torsten Reuter, Reuter, Torsten, Rainer Schwabe +1
Computer Science · #62D99 #62J12 #Bayesian Methods and Mixture Models #FOS: Mathematics #Primary: 62K05. Secondary: 62R07 #Statistics Theory (math.ST)
paper · pdf · doi:10.48550/arxiv.2403.18432
openalex publication_date 2024/03/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
The goal of subsampling is to select an informative subset of all observations, when using the full data for statistical analysis is not viable. We construct locally D -optimal subsampling designs under a Poisson regression model with a log link in one covariate. A Representation of the support of locally D -optimal subsampling designs is established. We make statements on scale-location transformations of the covariate that require a simultaneous transformation of the regression parameter. The performance of the methods is demonstrated by illustrating examples. To show the advantage of the optimal subsampling designs, we examine the efficiency of uniform random subsampling as well as of two heuristic designs. Further, the efficiency of locally D -optimal subsampling designs is studied when the parameter is misspecified.