logl values associated with equally weighted samples about ultranest HOT 4 CLOSED

That's fine and how the equally weighted posterior samples are created internally (in all nested samplers).

If you need the likelihood of the posterior samples, I suspect you are doing something dodgy though ... What do you need it for?

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Mostly bookkeeping actually: I'm optimizing a larger model for which I recompute the full output on the equally weighted posterior samples (to speed-up during optimization, I only compute the subset of the output relevant for comparing to the actual observables we have).

I'm now curious what the outputs actually look like for the samples that produced highest likelihood. Hence it seems useful to still have the likelihoods associated with the samples.

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Yeah, considering the likelihood isn't really a Bayesian approach because it doesn't consider the prior density, I'd usually just grab the first hundred or so posterior points to work with (e.g., plot the model fit). In many cases both approaches end up behaving similarly though.

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Yes, of course - thanks for the clarifications!

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