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ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.

J Med Internet Res
Ruta MR, Gaidici T, Irwin C, Lifshitz J.
europepmc   +1 more source

Correction: Toward a Domain-Overarching Metadata Schema for Making Health Research Studies FAIR (Findable, Accessible, Interoperable, and Reusable): Development of the NFDI4Health Metadata Schema.

JMIR Med Inform
Abaza H, Shutsko A, Klopfenstein SAI, Vorisek CN, Schmidt CO, Brünings-Kuppe C, Clemens V, Darms J, Hanß S, Intemann T, Jannasch F, Kasbohm E, Lindstädt B, Löbe M, Nimptsch K, Nöthlings U, Ocanto MG, Osei TB, Perrar I, Peters M, Pischon T, Sax U, Schulze MB, Schwarz F, Schwedhelm C, Thun S, Waltemath D, Zeleke AA, Müller W, Golebiewski M.   +29 more
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Asymptotic properties of conditional U-statistics using delta sequences

Communications in Statistics - Theory and Methods, 2023
Stute (1991) introduced a class of so-called conditional U-statistics, which may be viewed as a generalization of the Nadaraya-Watson estimates of a regression function. Stute proved their strong pointwise consistency to: r(k)(φ,t):=E[φ(Y1,…,Yk)|(X1,…,Xk)
S. Bouzebda, Amel Nezzal
semanticscholar   +1 more source

CLT For U-statistics With Growing Dimension

, 2022
The purpose of this paper is to present a general triangular array Central Limit Theorem for U -statistics, where the kernel hk(x1, . . . , xk) and its dimension k may increase with the sample size.
Cyrus DiCiccio, Joseph P. Romano
semanticscholar   +1 more source

On the uniform-in-bandwidth consistency of the general conditional U-statistics based on the copula representation

, 2021
Stute [Ann. Probab. 19 (1991) 812–825] introduced a class of estimators called conditional U-statistics of In the present work, we provide a new class of estimators of conditional U-statistics.
S. Bouzebda, I. Elhattab, B. Nemouchi
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Invariant U-statistics

Communications in Statistics - Theory and Methods, 1986
For a class of distributions which are invariant under a group of transformations, we propose an estimator ot an estimable parameter. The estimator, which we call the invariant U-statistic, is the uniformly minimum variance unbiased estimator of the corresponding estimable parameter for the class of all continuous distributions which are invariant ...
Yoshihiko Maesono, Hajime Yamato
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Uniform consistency and uniform in bandwidth consistency for nonparametric regression estimates and conditional U-statistics involving functional data

, 2020
W. Stute [(1991), Annals of Probability, 19, 812–825] introduced a class of so-called conditional U-statistics, which may be viewed as a generalisation of the Nadaraya–Watson estimates of a regression function.
S. Bouzebda, B. Nemouchi
semanticscholar   +1 more source

Quantifying Uncertainty in Neural Network Ensembles using U-Statistics

IEEE International Joint Conference on Neural Network, 2020
Quantifying uncertainty is critically important to many applications of predictive modeling. In this paper we apply a recently developed method that uses U-statistics as a basis for estimating uncertainty in ensemble regressors to the case of neural ...
Jordan Schupbach, John W. Sheppard, Tyler Forrester   +2 more
semanticscholar   +1 more source

Estimate of variance of u-statistics [PDF]

Communications in Statistics - Theory and Methods, 1992
Let g(x1,… , xk) be a symmetric function with k arguments. Let U be a U-statistic based on a random sample of size n with kernel function g . In this paper, the problem of estimating var(U) is considered. Several estimators are compared by computer simulations and we conclude that two estimators, one is constructed as a U-statistic and the other is the
Shingo Shirahata, Yuji Sakamoto
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