Estimate each one-dimensional marginal posterior from its individual experiment's weighted samples, for example by weighted kernel density estimation. Combining that density estimate with the individual evidence estimate gives
Their product with can be normalized on the one-dimensional space, avoiding all joint nuisance-parameter sampling.

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