loo_pit for discrete data

[aloctavodia]

We recently introducing a smoothing step for discrete data in plot_pbv, this does the same but for loo_pit. See example below. I am omitting plot from plot_pbv, because they were part of a previous PR.

• Follows official PR format
• Includes a sample plot to visually illustrate the changes (only for plot-related functions)
• New features are properly documented (with an example if appropriate)?
• Includes new or updated tests to cover the new feature
• Code style correct (follows pylint and black guidelines)
• Changes are listed in changelog

binomial well-calibrated old

binomial well-calibrated new

binomial bad-calibrated old

binomial bad-calibrated new

Poisson well-calibrated old

Poisson well-calibrated new

poisson bad-calibrated old

poisson bad-calibrated new

[codecov]

Codecov Report

Merging #1500 (213651f) into master (2d202de) will decrease coverage by 0.06%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #1500      +/-   ##
==========================================
- Coverage   91.97%   91.91%   -0.07%     
==========================================
  Files         105      105              
  Lines       11239    11251      +12     
==========================================
+ Hits        10337    10341       +4     
- Misses        902      910       +8     

Impacted Files	Coverage Δ
arviz/plots/backends/bokeh/bpvplot.py	82.35% <100.00%> (-0.83%)	⬇️
arviz/plots/backends/matplotlib/bpvplot.py	82.07% <100.00%> (-0.81%)	⬇️
arviz/stats/stats.py	96.12% <100.00%> (-0.29%)	⬇️
arviz/stats/stats_utils.py	96.71% <100.00%> (+0.10%)	⬆️
arviz/wrappers/base.py	17.54% <0.00%> (-3.61%)	⬇️
arviz/data/io_pymc3.py	92.19% <0.00%> (-0.25%)	⬇️
arviz/data/base.py	97.70% <0.00%> (ø)
arviz/data/io_json.py	66.66% <0.00%> (ø)
arviz/data/io_pystan.py	96.00% <0.00%> (ø)
... and 2 more

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