Zobrazeno 1 - 10
of 293
pro vyhledávání: '"van der Vaart, Aad"'
We consider nonparametric estimation of the distribution function $F$ of squared sphere radii in the classical Wicksell problem. Under smoothness conditions on $F$ in a neighborhood of $x$, in \cite{21} it is shown that the Isotonic Inverse Estimator
Externí odkaz:
http://arxiv.org/abs/2410.14263
Given a mild solution $X$ to a semilinear stochastic partial differential equation (SPDE), we consider an exponential change of measure based on its infinitesimal generator $L$, defined in the topology of bounded pointwise convergence. The changed me
Externí odkaz:
http://arxiv.org/abs/2409.08057
We consider the accuracy of an approximate posterior distribution in nonparametric regression problems by combining posterior distributions computed on subsets of the data defined by the locations of the independent variables. We show that this appro
Externí odkaz:
http://arxiv.org/abs/2312.14130
Combining test statistics from independent trials or experiments is a popular method of meta-analysis. However, there is very limited theoretical understanding of the power of the combined test, especially in high-dimensional models considering compo
Externí odkaz:
http://arxiv.org/abs/2310.19541
We consider nonparametric estimation in Wicksell's problem which has relevant applications in astronomy for estimating the distribution of the positions of the stars in a galaxy given projected stellar positions and in material sciences to determine
Externí odkaz:
http://arxiv.org/abs/2310.05463
We consider a Bayesian approach for the recovery of scalar parameters arising in inverse problems. We consider a general signal-in white noise model where we have access to two independent noisy observations of a function, and of a linear transformat
Externí odkaz:
http://arxiv.org/abs/2310.02883
We derive a Bernstein von-Mises theorem in the context of misspecified, non-i.i.d., hierarchical models parametrized by a finite-dimensional parameter of interest. We apply our results to hierarchical models containing non-linear operators, including
Externí odkaz:
http://arxiv.org/abs/2308.07803
In causal inference, sensitivity analysis is important to assess the robustness of study conclusions to key assumptions. We perform sensitivity analysis of the assumption that missing outcomes are missing completely at random. We follow a Bayesian ap
Externí odkaz:
http://arxiv.org/abs/2305.06816
Caliper matching is used to estimate causal effects of a binary treatment from observational data by comparing matched treated and control units. Units are matched when their propensity scores, the conditional probability of receiving treatment given
Externí odkaz:
http://arxiv.org/abs/2304.08373
Autor:
Chen, X. Gregory, van der Vaart, Aad
We review and contrast frequentist and Bayesian definitions of tolerance regions. We give conditions under which for large samples a Bayesian region also has frequentist validity, and study the latter for smaller samples in a simulation study. We dis
Externí odkaz:
http://arxiv.org/abs/2209.08496