Adaptive quantile computation for Brownian bridge in change-point analysis
| Autor: | Jürgen Franke, André Herzwurm, Mario Hefter, Stefanie Schwaar, Klaus Ritter |
|---|---|
| Přispěvatelé: | Publica |
| Rok vydání: | 2022 |
| Předmět: |
FOS: Computer and information sciences
Statistics and Probability Discretization Applied Mathematics Computation CUSUM Brownian bridge Statistics - Computation change-point problem Sup-norm quantiles Computational Mathematics symbols.namesake Uniform norm Computational Theory and Mathematics weighted CUSUM statistic Monte Carlo algorithm symbols weighted Brownian bridge Applied mathematics Gaussian process Computation (stat.CO) adaptive discretization Quantile Mathematics |
| Zdroj: | Computational Statistics & Data Analysis. 167:107375 |
| ISSN: | 0167-9473 |
| DOI: | 10.1016/j.csda.2021.107375 |
| Popis: | As an example for the fast calculation of distributional parameters of Gaussian processes, a new Monte Carlo algorithm for the computation of quantiles of the supremum norm of weighted Brownian bridges is proposed. As it is known, the corresponding distributions arise asymptotically for weighted CUSUM statistics for change-point detection. The new algorithm employs an adaptive (sequential) time discretization for the trajectories of the Brownian bridge. A simulation study shows that the new algorithm by far outperforms the standard approach, which employs a uniform time discretization. |
| Databáze: | OpenAIRE |
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