Add function for taking expectations wrt smoothed weights

[sethaxen]

This PR adds the API function expectation, which allows one to take some expectation wrt to PSIS-smoothed weights. This is the main function needed to compute expectations wrt LOO posteriors, though it is not limited to this application.

Some notes:

• Currently the expectand must have shape (draws, [chains, [params...]]), i.e. it might share the data dimensions. This allows the function to be used for data-dependent scalar expectations e.g. loo_pit. However, one might have data-independent dimensions with or without data dimensions, e.g. for computing the LOO posterior means of all marginals. Supporting this could require a keyword that specifies which (trailing) dims in x are unrelated to the data or draws.
• Currently we do not compute function-specific diagnostics. This requires something like Make smoothing optional #23, so that we can compute diagnostics without then smoothing.
• Maybe a better way to compute expectations like mean is on the log-scale. However, this would require us to limit which expectations we can support.

[codecov]

Codecov Report

Attention: 24 lines in your changes are missing coverage. Please review.

Comparison is base (3e6e5ec) 97.44% compared to head (7dea818) 89.59%.

Files	Patch %	Lines
src/expectation.jl	0.00%	24 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #61      +/-   ##
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- Coverage   97.44%   89.59%   -7.85%     
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  Files           6        7       +1     
  Lines         274      298      +24     
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  Hits          267      267              
- Misses          7       31      +24     

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