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- W4289389785 abstract "Parallel tempering is popular method for allowing MCMC algorithms to properly explore a $d$-dimensional multimodal target density. One problem with traditional power-based parallel tempering for multimodal targets is that the proportion of probability mass associated to the modes can change for different inverse-temperature values, sometimes dramatically so. Complementary work by the authors proposes a novel solution involving auxiliary targets that preserve regional weight upon powering up the density. This paper attempts to address the question of how to choose the temperature spacings in an optimal way when using this type of weight-preserving approach.The problem is analysed in a tractable setting for computation of the expected squared jumping distance which can then be optimised with regards to a tuning parameter. The conclusion is that for an appropriately constructed regionally weight-preserved tempering algorithm targeting a $d$-dimensional target distribution, the consecutive temperature spacings should behave as $mathcal{O}left(d^{-1/2}right)$ and this induces an optimal acceptance rate for temperature swap moves that lies in the interval $[0,0.234]$." @default.
- W4289389785 created "2022-08-02" @default.
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- W4289389785 date "2018-10-13" @default.
- W4289389785 modified "2023-09-26" @default.
- W4289389785 title "Optimal Temperature Spacing for Regionally Weight-preserving Tempering" @default.
- W4289389785 doi "https://doi.org/10.48550/arxiv.1810.05845" @default.
- W4289389785 hasPublicationYear "2018" @default.
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