Susceptibilities quantify observable responses to data perturbations in statistical models, with estimators proven consistent and asymptotically unbiased for large n.
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Susceptibilities defined via posterior covariances serve as the Jacobian for mapping data distributions to structural coordinates in Bayesian learning, with pseudo-inverse solving for desired structural changes.
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Linear Response Estimators for Singular Statistical Models
Susceptibilities quantify observable responses to data perturbations in statistical models, with estimators proven consistent and asymptotically unbiased for large n.
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Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
Susceptibilities defined via posterior covariances serve as the Jacobian for mapping data distributions to structural coordinates in Bayesian learning, with pseudo-inverse solving for desired structural changes.