# Adaptive Kernel Density Estimation proposal in gravitational wave data analysis

@inproceedings{Falxa2022AdaptiveKD, title={Adaptive Kernel Density Estimation proposal in gravitational wave data analysis}, author={Mikel Falxa and Stanislav Babak and Maude Le Jeune}, year={2022} }

Markov Chain Monte Carlo approach is frequently used within Bayesian framework to sample the target posterior distribution. Its e ﬃ ciency strongly depends on the proposal used to build the chain. The best jump proposal is the one that closely resembles the unknown target distribution, therefore we suggest an adaptive proposal based on Kernel Density Estimation (KDE). We group parameters of the model according to their correlation and build KDE based on the already accepted points for each…

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