Berry Esseen type bounds to the normal, based on zeroand size-bias couplings, are derived using Stein’s method. The zero biasing bounds are illustrated with an application to combinatorial central limit theorems where the random permutation has either the uniform distribution or one which is constant over permutations with the same cycle type and having no fixed points. The size biasing bounds ...

Consider a Markov chain X assumed to be positive recurrent with limiting probability distribution used to construct a U-statistics. Whereas the asymptotic properties of U -statistics based on independent and identically distributed data are well understood since the sixties the study of this speci…c class of statistics for dependent data has recently received special attention in the statistica...

Deformable models are an important tool in computer vision. A deformable model is a curve (in two dimensions) or a surface (in three dimensions), whose shape, position, and orientation are controlled through a set of parameters. They can represent manufactured objects, human faces and skeletons, and even bodies of fluid. Deformable models restrict the family of possible solutions in tracking an...

STATISTICAL CUE ESTIMATION FOR MODEL-BASED SHAPE AND MOTION TRACKING Siome Goldenstein Supervisor: Dimitris Metaxas Vision-based tracking of moving objects is important in many applications, ranging from sports and medicine to security and recognition of human action. In this dissertation we discuss novel methods for statistical deformable model tracking. Our main contribution is a method to es...

* Correspondence: lym1019@163. com Department of Mathematics, Shangrao Normal University, Shangrao 334001, China Full list of author information is available at the end of the article Abstract Consider the semiparametric regression model Yi = xi b + g (ti) + εi, i = 1, . . . , n, where the linear process errors εi = ∑∞ j=−∞ ajei−j with ∑∞ j=−∞ ∣∣aj∣∣ < ∞ , and {ei} are identically distributed a...

Suppose that the (normalised) partial sum of a stationary sequence converges to standard normal random variable. Given sufficiently moments, when do we have rate convergence n−1∕2 in uniform metric, other words, optimal Berry-Esseen bound? We study this question quite general framework and find (almost) sharp dependence conditions. The result applies many different processes dynamical systems. ...

Millaisia näkökulmia tuoreet ajanhallinnan tietokirjat antavat itsestä huolehtimiseen, ajankäyttöön, ekokriisiin ja suoritusyhteiskuntaan? Esseen lähteinä on kaksi eri tavalla aikaa lähestyvää teosta, Brian O’Connorin Joutilaisuus Leo Straniuksen Tehokkuuden taika. Optimoinnin sijaan meidän tulee tarjota itsellemme joutilasta haahuilua, jonka ainoa tarkoitus läsnä oleminen elämisen ihmettelystä...

Abstract Let $(Z_n)_{n\geq0}$ be a supercritical Galton–Watson process. Consider the Lotka–Nagaev estimator for offspring mean. In this paper we establish self-normalized Cramér-type moderate deviations and Berry–Esseen bounds estimator. The results are believed to optimal or near-optimal.

We establish a Berry–Esseen bound for general multivariate nonlinear statistics by developing new multivariate-type randomized concentration inequality. The is the best possible many known statistics. As applications, bounds M-estimators and averaged stochastic gradient descent algorithms are obtained.