Add error pipeline and adapt documentation

[rhugonnet]

Summary of changes in spatialstats.py:

Documentation updated with changes of this branch is here: https://xdem-rhugonnet.readthedocs.io/en/error_pipeline/

This PR:

• Adds the number_effective_samples wrapper function and related tests,
• Adds the two_step_standardization function to consistently rescale the standardization after interp_nd_binning and related tests,
• Adds the infer_heteroscedasticity_from_stable function (wrapper around Raster and Vector objects) and the estimate_model_heteroscedasticity function (wrapper of nd_binning, interp_nd_binning and two_step_standardization with np.ndarray) functions and tests,
• Adds the infer_spatial_correlation_from_stable (wrapper around Raster and Vector objects) and estimate_model_spatial_correlation (wrapper of sample_empirical_variogram and fit_sum_model_variogram with np.ndarray) wrapper function and tests,
• Add the spatial_error_propagation wrapper function (wrapper around Raster and Vector objects) and tests,
• Adds short, basic gallery examples "Elevation error map" in plot_infer_heterosc, "Spatial correlation of errors" in plot_infer_spatial_correlation and "Spatial propagation of elevation errors" in plot_spatial_error_propagation for each of the 3 wrapper functions that work directly with Raster and Vector objects with all steps included,
• Updates the existing advanced gallery examples with the new functions, references and naming (trying to shorten content that was a bit long, now referencing to Hugonnet et al. (2022) for lots of things). This results in the renaming of "Non-stationarity of elevation measurement errors" into "Estimation and modelling of elevation heteroscedasticity" now in plot_variogram_estimation_modelling.py, renaming of "Spatial correlation of elevation measurement errors" into "Estimation and modelling of spatial variograms" in plot_variogram_estimation_modelling.py;
• Updates the documentation page on spatial statistics with the new reference and terms for consistency across the package.

Resolves #256

[adehecq]

Apart from mostly minor comments, this looks all good!
Fantastic work !! 👏