A latent density approach to interpolation improves on previous methods by accounting for uncertainty of model inputs, allowing researchers to construct income segregation indices from ACS tract-level distributions.
A latent density approach to interpolation improves on previous methods by accounting for uncertainty of model inputs, allowing researchers to construct income segregation indices from ACS tract-level distributions.
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