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A new method for analyzing high-dimensional categorical data, Linear Latent Structure (LLS) analysis, is presented. LLS models belong to the family of latent structure models, which are mixture distribution models constrained to satisfy the…

Probability · Mathematics 2007-06-13 Mikhail Kovtun , Igor Akushevich , Kenneth G. Manton , H. Dennis Tolley

The nature of the alignment with gaps corresponding to a longest common subsequence (LCS) of two independent iid random sequences drawn from a finite alphabet is investigated. It is shown that such an optimal alignment typically matches…

Probability · Mathematics 2016-04-22 C. Houdré , H. Matzinger

In this article we develop a new sequential Monte Carlo (SMC) method for multilevel (ML) Monte Carlo estimation. In particular, the method can be used to estimate expectations with respect to a target probability distribution over an…

Computation · Statistics 2017-03-16 Alexandros Beskos , Ajay Jasra , Kody Law , Youssef Marzouk , Yan Zhou

Binary Sidel'nikov-Lempel-Cohn-Eastman sequences (or SLCE sequences) over F 2 have even period and almost perfect autocorrelation. However, the evaluation of the linear complexity of these sequences is really difficult. In this paper, we…

Information Theory · Computer Science 2017-02-21 Qi Zhang , Jing Yang

This thesis is devoted to studying estimates of the least common multiple of some integer sequences. Our study focuses on effective bounding of the $\mathrm{lcm}$ of some class of quadratic sequences, as well as arithmetic progressions and…

Number Theory · Mathematics 2020-12-11 Sid Ali Bousla

Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear mixed-effects models with high-dimensional…

Methodology · Statistics 2021-03-10 Sai Li , Tony T. Cai , Hongzhe Li

In this paper we give an overview of recent results on (upper and lower) discrepancy estimates for (concrete) sequences in the unit-cube. In particular we also give an overview of discrepancy estimates for certain classes of hybrid…

Number Theory · Mathematics 2014-07-10 Gerhard Larcher

In the framework of uncertainty quantification, we consider a quantity of interest which depends non-smoothly on the high-dimensional parameter representing the uncertainty. We show that, in this situation, the multilevel Monte Carlo…

Numerical Analysis · Mathematics 2017-06-27 Laura Scarabosio

The notion of lacunary infinite numerical sequence is introduced. It is shown that for an arbitrary linear difference operator L with coefficients belonging to the set R of infinite numerical sequences, a criterion (i.e., a necessary and…

Symbolic Computation · Computer Science 2023-11-07 Sergei Abramov , Gleb Pogudin

We propose a two-step procedure to detect cointegration in high-dimensional settings, focusing on sparse relationships. First, we use the adaptive LASSO to identify the small subset of integrated covariates driving the equilibrium…

Methodology · Statistics 2026-03-05 Jesus Gonzalo , Jean-Yves Pitarakis

Consider generalized adapted stochastic integrals with respect to independently scattered random measures with second moments. We use a decoupling technique, known as the "principle of conditioning", to study their stable convergence…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Murad S. Taqqu

This work proposes new inference methods for a regression coefficient of interest in a (heterogeneous) quantile regression model. We consider a high-dimensional model where the number of regressors potentially exceeds the sample size but a…

Statistics Theory · Mathematics 2017-10-05 Alexandre Belloni , Victor Chernozhukov , Kengo Kato

This paper studies a generalization of hyperinterpolation over the high-dimensional unit cube. Hyperinterpolation of degree \( m \) serves as a discrete approximation of the \( L_2 \)-orthogonal projection of the same degree, using Fourier…

Numerical Analysis · Mathematics 2025-07-08 Congpei An , Mou Cai , Takashi Goda

We study uniform consistency in nonparametric mixture models as well as closely related mixture of regression (also known as mixed regression) models, where the regression functions are allowed to be nonparametric and the error…

Statistics Theory · Mathematics 2022-12-29 Bryon Aragam , Ruiyi Yang

High-dimensional probability density estimation for inference suffers from the "curse of dimensionality". For many physical inference problems, the full posterior distribution is unwieldy and seldom used in practice. Instead, we propose…

Machine Learning · Statistics 2020-11-13 Niall Jeffrey , Benjamin D. Wandelt

This is basically a review of the field of Quasi-Monte Carlo intended for computational physicists and other potential users of quasi-random numbers. As such, much of the material is not new, but is presented here in a style hopefully more…

High Energy Physics - Phenomenology · Physics 2010-11-11 Fred James , Jiri Hoogland , Ronald Kleiss

Based on the Lippmann-Schwinger equation approach, a generalized L\"uscher's formula in 1+1 dimensions for two particles scattering in both the elastic and coupled-channel cases in moving frames is derived. A 2D coupled-channel scattering…

High Energy Physics - Lattice · Physics 2013-08-09 Peng Guo

We consider the demixing problem of two (or more) high-dimensional vectors from nonlinear observations when the number of such observations is far less than the ambient dimension of the underlying vectors. Specifically, we demonstrate an…

Machine Learning · Statistics 2017-01-25 Mohammadreza Soltani , Chinmay Hegde

We investigate random spatially coupled low-density parity-check (SC-LDPC) code ensembles over finite fields. Under different variable-node edge-spreading rules, the random Tanner graphs of several coupled ensembles are defined by multiple…

Information Theory · Computer Science 2026-01-01 Jiaxin Lyu , Guanghui He

In this note, we study a concatenation of quasi-Monte Carlo and plain Monte Carlo rules for high-dimensional numerical integration in weighted function spaces. In particular, we consider approximating the integral of periodic functions…

Numerical Analysis · Mathematics 2022-06-27 Takashi Goda