IVFR extends global Fréchet regression to endogenous covariates via projection of IV-weighted quantile curves onto valid distributions in 2-Wasserstein space, with weak convergence to a Gaussian process and valid multiplier bootstrap for uniform inference.
arXiv preprint arXiv:2402.14763 , year=
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Introduces conditional autoregressive models for spatially dependent functional data with consistent covariance estimation via conditional centering and superconsistent, asymptotically normal estimation of the spatial dependence parameter under an expanding lattice.
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IV regression with distribution-valued outcomes
IVFR extends global Fréchet regression to endogenous covariates via projection of IV-weighted quantile curves onto valid distributions in 2-Wasserstein space, with weak convergence to a Gaussian process and valid multiplier bootstrap for uniform inference.
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A new class of functional conditional autoregressive models
Introduces conditional autoregressive models for spatially dependent functional data with consistent covariance estimation via conditional centering and superconsistent, asymptotically normal estimation of the spatial dependence parameter under an expanding lattice.