A modified PCA method compresses sampled nuisance priors in Bayesian inference by projecting out likelihood-insensitive modes, applied to photometric redshift distributions for DES weak lensing and galaxy clustering analyses.
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Dimensional reduction for sampled priors and application to photometric redshift distributions
A modified PCA method compresses sampled nuisance priors in Bayesian inference by projecting out likelihood-insensitive modes, applied to photometric redshift distributions for DES weak lensing and galaxy clustering analyses.