2011/05/10 by Rohit K. Patra, Rohit Kumar Patra, Emilio Seijo +4
Mathematics · #Advanced Statistical Methods and Models #Applications (stat.AP) #FOS: Computer and information sciences #FOS: Mathematics #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST) #math.ST #stat.AP #stat.TH
paper · pdf · doi:10.48550/arxiv.1105.1976
openalex publication_date 2011/05/10 · arxiv created 2015/12/18 · arxiv updated 2015/12/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we study the applicability of the bootstrap to do inference on Manski's maximum score estimator under the full generality of the model. We propose three new, model-based bootstrap procedures for this problem and show their consistency. Simulation experiments are carried out to evaluate their performance and to compare them with subsampling methods. Additionally, we prove a uniform convergence theorem for triangular arrays of random variables coming from binary choice models, which may be of independent interest.