MSFA clusters tensor-variate spatial data via a flexible I-spline spatial-decay covariance plus matrix factor analyzers, estimated by AECM+GLS, and recovers group-specific spatial patterns better than standard mixtures.
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Closed-form mth Gini and U-statistic bias formulas under gamma mixtures, with asymptotic unbiasedness, consistency, and normality under a common rate.
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Mixtures of spatial factor analyzers for tensor-variate data
MSFA clusters tensor-variate spatial data via a flexible I-spline spatial-decay covariance plus matrix factor analyzers, estimated by AECM+GLS, and recovers group-specific spatial patterns better than standard mixtures.
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Income inequality estimation with gamma mixtures
Closed-form mth Gini and U-statistic bias formulas under gamma mixtures, with asymptotic unbiasedness, consistency, and normality under a common rate.