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Conference Paper: Efficient Monte Carlo Evaluation of Resampling-based Hypothesis Tests
Title | Efficient Monte Carlo Evaluation of Resampling-based Hypothesis Tests |
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Authors | |
Keywords | Bootstrap test Monte Carlo sample power estimate permutation test resampling |
Issue Date | 2018 |
Citation | XXI International Symposium on Mathematical Methods Applied to the Sciences (XXI SIMMAC) & III Latin American Conference on Statistical Computing (III LACSC), San Jose, Costa Rica, 27 February - 2 March 2018 How to Cite? |
Abstract | Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this
procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this talk, we first investigate the asymptotic properties of the pooling resampling-based method, and then propose a novel Monte Carlo evaluation procedure namely the n-times pooling resampling-based method. Theorems as well as simulations show that the proposed method can give smaller or comparable root mean squared errors and bias with much less computing time, thus can be strongly recommended especially for evaluating highly computationally intensive hypothesis testing procedures. |
Description | Keynote Speech - Plenary Talk - Session: Conference LACSC 1 (C-LACSC) - no. 128 |
Persistent Identifier | http://hdl.handle.net/10722/296461 |
DC Field | Value | Language |
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dc.contributor.author | Fung, TWK | - |
dc.date.accessioned | 2021-02-25T07:15:48Z | - |
dc.date.available | 2021-02-25T07:15:48Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | XXI International Symposium on Mathematical Methods Applied to the Sciences (XXI SIMMAC) & III Latin American Conference on Statistical Computing (III LACSC), San Jose, Costa Rica, 27 February - 2 March 2018 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296461 | - |
dc.description | Keynote Speech - Plenary Talk - Session: Conference LACSC 1 (C-LACSC) - no. 128 | - |
dc.description.abstract | Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this talk, we first investigate the asymptotic properties of the pooling resampling-based method, and then propose a novel Monte Carlo evaluation procedure namely the n-times pooling resampling-based method. Theorems as well as simulations show that the proposed method can give smaller or comparable root mean squared errors and bias with much less computing time, thus can be strongly recommended especially for evaluating highly computationally intensive hypothesis testing procedures. | - |
dc.language | eng | - |
dc.relation.ispartof | XXI International Symposium on Mathematical Methods Applied to the Sciences (XXI SIMMAC) & III Latin American Conference on Statistical Computing (III LACSC), 2018 | - |
dc.relation.ispartof | III Latin American Conference on Statistical Computing | - |
dc.subject | Bootstrap test | - |
dc.subject | Monte Carlo sample | - |
dc.subject | power estimate | - |
dc.subject | permutation test | - |
dc.subject | resampling | - |
dc.title | Efficient Monte Carlo Evaluation of Resampling-based Hypothesis Tests | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Fung, TWK: wingfung@hkucc.hku.hk | - |
dc.identifier.authority | Fung, TWK=rp00696 | - |
dc.identifier.hkuros | 300047 | - |