General Bootstrap for Dual ϕ-Divergence Estimates
Copyright policy )General Bootstrap for Dual ϕ-Divergence Estimates
A general notion of bootstrappedϕ-divergence estimates constructed by exchangeably weighting sample is introduced. Asymptotic properties of these generalized bootstrappedϕ-divergence estimates are obtained, by means of the empirical process theory, which are applied to construct the bootstrap confidence set with asymptotically correct coverage probability. Some of practical problems are discussed, including, in particular, the choice of escort parameter, and several examples of divergences are investigated. Simulation results are provided to illustrate the finite sample performance of the proposed estimators.
FOS: Computer and information sciences, [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], [MATH.MATH-FA] Mathematics [math]/Functional Analysis [math.FA], Computational problems in statistics, Mathematics - Statistics Theory, Statistics Theory (math.ST), Statistical aspects of information-theoretic topics, QA273-280, Methodology (stat.ME), Nonparametric tolerance and confidence regions, FOS: Mathematics, Nonparametric statistical resampling methods, Nonparametric estimation, Probabilities. Mathematical statistics, Statistics - Methodology
FOS: Computer and information sciences, [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], [MATH.MATH-FA] Mathematics [math]/Functional Analysis [math.FA], Computational problems in statistics, Mathematics - Statistics Theory, Statistics Theory (math.ST), Statistical aspects of information-theoretic topics, QA273-280, Methodology (stat.ME), Nonparametric tolerance and confidence regions, FOS: Mathematics, Nonparametric statistical resampling methods, Nonparametric estimation, Probabilities. Mathematical statistics, Statistics - Methodology
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