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In this paper, we study finite-sample properties of the least squares estimator in first order autoregressive processes. By leveraging a result from decoupling theory, we derive upper bounds on the probability that the estimate deviates by…

Statistics Theory · Mathematics 2020-05-26 Rodrigo A. González , Cristian R. Rojas

The perimeter and area generating functions of exactly solvable polygon models satisfy q-functional equations, where q is the area variable. The behaviour in the vicinity of the point where the perimeter generating function diverges can…

Statistical Mechanics · Physics 2008-08-28 C. Richard , A. J. Guttmann

One of the major challenges in finite element methods is the mitigation of spurious oscillations near sharp layers and discontinuities known as the Gibbs phenomenon. In this article, we propose a set of functionals to identify spurious…

Numerical Analysis · Mathematics 2023-03-09 M. ten Eikelder , S. Stoter , Y. Bazilevs , D. Schillinger

We survey the main results of approximation theory for adaptive piecewise polynomial functions. In such methods, the partition on which the piecewise polynomial approximation is defined is not fixed in advance, but adapted to the given…

Numerical Analysis · Mathematics 2015-03-17 Albert Cohen , Jean-Marie Mirebeau

We consider bounded weak solutions to the Burgers equation for which every entropy dissipation is representable by a measure and we prove that all these measures are concentrated on the graphs of countably many Lipschitz curves. The main…

Analysis of PDEs · Mathematics 2020-04-22 Elio Marconi

Usually, given a continuous-time nonlinear model, a closed form solution for an exact discretization cannot be found explicitly, originating the need of approximating discrete-time models. This note studies the preservation of the Lipschitz…

Systems and Control · Computer Science 2020-04-21 Masoud Abbaszadeh

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

We prove best approximation error estimates for discontinuous piecewise polynomial approximation in fractional Sobolev spaces on non-Lipschitz meshes of non-Lipschitz domains. In particular, the boundary of the domain, and the boundaries of…

Numerical Analysis · Mathematics 2026-03-12 D P Hewett

This paper proposes a tractable family of remainder-form mixed-monotone decomposition functions that are useful for over-approximating the image set of nonlinear mappings in reachability and estimation problems. Our approach applies to a…

Optimization and Control · Mathematics 2024-06-25 Mohammad Khajenejad , Sze Zheng Yong

We propose new optimal estimators for the Lipschitz frontier of a set of points. They are defined as kernel estimators being sufficiently regular, covering all the points and whose associated support is of smallest surface. The estimators…

Methodology · Statistics 2011-03-31 Stéphane Girard , Anatoli Iouditski , Alexander Nazin

This paper concerns the approximation of probability measures on $\mathbf{R}^d$ with respect to the Kullback-Leibler divergence. Given an admissible target measure, we show the existence of the best approximation, with respect to this…

Probability · Mathematics 2017-06-26 Yulong Lu , Andrew M. Stuart , Hendrik Weber

The problem of super-resolution in general terms is to recuperate a finitely supported measure $\mu$ given finitely many of its coefficients $\hat{\mu}(k)$ with respect to some orthonormal system. The interesting case concerns situations,…

Functional Analysis · Mathematics 2019-07-12 H. N. Mhaskar

It is a common contention that it is an ``impossible mission'' to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such…

Statistics Theory · Mathematics 2007-08-02 Xinjia Chen

We consider the Monge problem of optimal transport between a compactly supported source measure and a target probability measure with unbounded support. We consider the convergence of optimal maps and potential functions when the target…

Numerical Analysis · Mathematics 2026-03-03 Axel G. R. Turnquist

We determine the scaling limit for permutations conditioned to have longest decreasing subsequence of length at most $d$. These permutations are also said to avoid the pattern $(d+1)d \cdots 2 1$ and they can be written as a union of $d$…

Probability · Mathematics 2023-01-09 Christopher Hoffman , Douglas Rizzolo , Erik Slivken

While the theory of operator approximation with any given accuracy is well elaborated, the theory of {best constrained} constructive operator approximation is still not so well developed. Despite increasing demands from applications this…

Optimization and Control · Mathematics 2018-11-09 Anatoli Torokhti , Pablo Soto-Quiros

In this note we study the Dirichlet problem associated with a version of prime end boundary of a bounded domain in a complete metric measure space equipped with a doubling measure supporting a Poincare inequality. We show the resolutivity…

Metric Geometry · Mathematics 2014-05-13 Dewey Estep , Nageswari Shanmugalingam

Shape restrictions such as monotonicity on functions often arise naturally in statistical modeling. We consider a Bayesian approach to the problem of estimation of a monotone regression function and testing for monotonicity. We construct a…

Statistics Theory · Mathematics 2020-08-05 Moumita Chakraborty , Subhashis Ghosal

We study the approximation of arbitrary distributions $P$ on $d$-dimensional space by distributions with log-concave density. Approximation means minimizing a Kullback--Leibler-type functional. We show that such an approximation exists if…

Statistics Theory · Mathematics 2011-10-17 Lutz Duembgen , Richard Samworth , Dominic Schuhmacher
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