Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
Biometrika , volume =
2 Pith papers cite this work. Polarity classification is still indexing.
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Derives augmented IPW estimators for occupation probabilities in coarsened multistate processes under coarsening at random, allowing time-varying confounders.
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Private Rate-Double-Robust Inference
Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
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Robust estimation of occupation probabilities for coarsened multistate processes
Derives augmented IPW estimators for occupation probabilities in coarsened multistate processes under coarsening at random, allowing time-varying confounders.