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In a typical two-phase design, a random sample is drawn from the target population in phase 1, during which only a subset of variables is collected. In phase 2, a subsample of the phase-1 cohort is selected, and additional variables are…

Methodology · Statistics 2026-03-02 Sky Qiu , Susan Gruber , Pamela A. Shaw , Brian D. Williamson , Mark J. van der Laan

This paper introduces a high-dimensional linear IV regression for the data sampled at mixed frequencies. We show that the high-dimensional slope parameter of a high-frequency covariate can be identified and accurately estimated leveraging…

Econometrics · Economics 2020-03-31 Andrii Babii

Quasi-Monte Carlo algorithms are studied for designing discrete approximations of two-stage linear stochastic programs. Their integrands are piecewise linear, but neither smooth nor lie in the function spaces considered for QMC error…

Optimization and Control · Mathematics 2014-10-31 H. Heitsch , H. Leövey , W. Römisch

The assumption of conditional independence among observed variables, primarily used in the Variational Autoencoder (VAE) decoder modeling, has limitations when dealing with high-dimensional datasets or complex correlation structures among…

Machine Learning · Computer Science 2023-10-26 Seunghwan An , Jong-June Jeon

Recently measurements on various spin-1/2 quantum magnets such as H$_3$LiIr$_2$O$_6$, LiZn$_2$Mo$_3$O$_8$, ZnCu$_3$(OH)$_6$Cl$_2$ and 1T-TaS$_2$ -- all described by magnetic frustration and quenched disorder but with no other common…

Strongly Correlated Electrons · Physics 2018-10-23 Itamar Kimchi , John P. Sheckelton , Tyrel M. McQueen , Patrick A. Lee

We provide lower error bounds for randomized algorithms that approximate integrals of functions depending on an unrestricted or even infinite number of variables. More precisely, we consider the infinite-dimensional integration problem on…

Numerical Analysis · Mathematics 2021-02-09 Michael Gnewuch

Intrinsic Gaussian Markov Random Fields (IGMRFs) can be used to induce conditional dependence in Bayesian hierarchical models. IGMRFs have both a precision matrix, which defines the neighbourhood structure of the model, and a precision, or…

Computation · Statistics 2021-11-18 Maria-Zafeiria Spyropoulou , James Bentham

We study non oscillating bifurcations of non homogeneous steady states of the Vlasov equation, a situation occurring in galactic models, or for Bernstein-Greene-Kruskal modes in plasma physics. We show that resonances are strongly…

Statistical Mechanics · Physics 2016-04-20 J. Barré , D. Métivier , Y. Y. Yamaguchi

Assigning significance in high-dimensional regression is challenging. Most computationally efficient selection algorithms cannot guard against inclusion of noise variables. Asymptotically valid p-values are not available. An exception is a…

Methodology · Statistics 2009-06-12 Nicolai Meinshausen , Lukas Meier , Peter Bühlmann

We identify the scaling limits for the sizes of the largest components at criticality for inhomogeneous random graphs when the degree exponent $\tau$ satisfies $\tau>4$. We see that the sizes of the (rescaled) components converge to the…

Probability · Mathematics 2009-09-09 Shankar Bhamidi , Remco van der Hofstad , Johan van Leeuwaarden

Regular variation is often used as the starting point for modeling multivariate heavy-tailed data. A random vector is regularly varying if and only if its radial part $R$ is regularly varying and is asymptotically independent of the angular…

Statistics Theory · Mathematics 2018-03-28 Phyllis Wan , Richard A. Davis

Bipartite Experiments are randomized experiments where the treatment is applied to a set of units (randomization units) that is different from the units of analysis, and randomization units and analysis units are connected through a…

The scrape-off layer power width (\lambda_q) is an important parameter for characterizing the divertor heat loads. Many experimental, theoretical, and numerical studies have been performed in recent years. In this paper, a 2D electrostatic…

Plasma Physics · Physics 2022-05-26 X. Liu , A. H. Nielsen , J. J. Rasmussen , V. Naulin , L. Wang , R. Ding , J. Li

We analyse a Monte Carlo particle method for the simulation of the calibrated Heston-type local stochastic volatility (H-LSV) model. The common application of a kernel estimator for a conditional expectation in the calibration condition…

Computational Finance · Quantitative Finance 2025-04-22 Christoph Reisinger , Maria Olympia Tsianni

We study the experimental constraints on strongly interacting vector-fermions compatible with the relaxion mechanism and investigate any possible tuning. The focus is on a minimal model and low confinement scale. More precisely, we study…

High Energy Physics - Phenomenology · Physics 2017-09-13 Hugues Beauchesne , Enrico Bertuzzo , Giovanni Grilli di Cortona

Interval censoring arises frequently in clinical, epidemiological, financial, and sociological studies, where the event or failure of interest is known only to occur within an interval induced by periodic monitoring. We formulate the…

Methodology · Statistics 2016-03-01 Donglin Zeng , Lu Mao , D. Y. Lin

Analytic phenomenological scaling is carried out for the random field Ising model in general dimensions using a bar geometry. Domain wall configurations and their decorated profiles and associated wandering and other exponents…

Condensed Matter · Physics 2009-10-28 R. B. Stinchcombe , E. D. Moore , S. L. A. de Queiroz

The velocity-space resolution required to accurately simulate kinetic phenomena in the 1D-1V Vlasov--Poisson system is generally not known a priori. In this work, we determine the upper bound on the resolution requirement for linear and…

Plasma Physics · Physics 2026-05-19 Noah K. Guberman , J. Coughlin , A. S. Joglekar

Kundu and Gupta (2007, Metrika, 65, 159 - 170) provided the analysis of Type-I hybrid censored competing risks data, when the lifetime distribution of the competing causes of failures follow exponential distribution. In this paper we…

Applications · Statistics 2017-07-18 Arnab Koley , D. Kundu , Ayon Ganguly

An important consideration for variable selection in interaction models is to design an appropriate penalty that respects hierarchy of the importance of the variables. A common theme is to include an interaction term only after the…

Statistics Theory · Mathematics 2016-03-31 Junlong Zhao , Chenlei Leng