Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP), bias-corrected bootstrap (BC), accelerated bias-corrected bootstrap (BCA) and a modified version of the standard bootstrap (MSB). Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP), bias-corrected bootstrap (BC), accelerated bias-corrected bootstrap (BCA) and a modified version of the standard bootstrap (MSB). Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Roberto S. Flowers-Cano (Autor:in) / Ruperto Ortiz-Gómez (Autor:in) / Jesús Enrique León-Jiménez (Autor:in) / Raúl López Rivera (Autor:in) / Luis A. Perera Cruz (Autor:in)
2018
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Monte Carlo Confidence Intervals for Complex Functions of Indirect Effects
British Library Online Contents | 2016
|Small Sampie Properties of Nonparametric Bootstrap t Confidence intervals
Taylor & Francis Verlag | 1997
|Confidence Intervals of Fit Indexes by Inverting a Bootstrap Test
British Library Online Contents | 2017
|