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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Introduces the MCB estimator for pointwise Wasserstein barycenter quantile estimation under sparse sampling by modeling the distribution of latent unit-level quantiles via marginal CDF distributions estimated with binomial mixtures, with consistency and asymptotic normality.
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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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Estimating the Wasserstein barycenter of one-dimensional distributions under sparse sampling
Introduces the MCB estimator for pointwise Wasserstein barycenter quantile estimation under sparse sampling by modeling the distribution of latent unit-level quantiles via marginal CDF distributions estimated with binomial mixtures, with consistency and asymptotic normality.