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A novel parametric predictive bootstrap method
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AI
DOI：10.1080/03610926.2025.2553732.png)
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Abstract
En 中文
Bootstrap methods are widely used statistical techniques known for their simplicity and good properties. This paper introduces a novel bootstrap method called the parametric predictive bootstrap (PP-B), which relies on parametric models and is designed for predictive inference. The PP-B method is evaluated in various scenarios and typically used with other bootstrap methods to assess its performance in estimation and prediction inference. Comparisons of PP-B with other bootstrap methods are made in terms of the coverage probabilities of confidence and prediction intervals. Simulation results indicate that PP-B excels in predictive inference due to its explicitly predictive nature.
Keywords:
Bootstrap
confidence intervals
prediction intervals
prediction regions
nonparametric predictive inference bootstrap
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C
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0.8
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221
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0
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