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Convergence Rates for Markov Chains [PDF]
SIAM Review, 1995 Summary: This is an expository paper that presents various ideas related to nonasymptotic rates of convergence for Markov chains. Such rates are of great importance for stochastic algorithms that are widely used in statistics and in computer science. They also have applications to analysis of card shuffling and other areas.
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Rate of Convergence Towards Semi-Relativistic Hartree Dynamics
, 2013 We consider the semi-relativistic system of $N$ gravitating Bosons with gravitation constant $G$. The time evolution of the system is described by the relativistic dispersion law, and we assume the mean-field scaling of the interaction where $N \to ...
A. Elgart +27 more
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Convergence Rates for Generalized Descents [PDF]
The Electronic Journal of Combinatorics, 2011 d-descents are permutation statistics that generalize the notions of descents and inversions. It is known that the distribution of d-descents of permutations of length n satisfies a central limit theorem as n goes to infinity. We provide an explicit formula for the mean and variance of these statistics and obtain bounds on the rate of convergence using
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Persistence in real exchange rate convergence [PDF]
Studies in Nonlinear Dynamics and Econometrics, 2014 AbstractIn this paper we use a long memory framework to examine the validity of the Purchasing Power Parity (PPP) hypothesis using both monthly and quarterly data for a panel of 47 countries over a 50 year period (1957–2009). The analysis focuses on the long memory parameter d that allows us to obtain different convergence classifications depending on ...
Thanasis Stengos, M. Ege Yazgan
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On Strong Convergence to Equilibrium for the Boltzmann Equation with Soft Potentials
, 2009 The paper concerns $L^1$- convergence to equilibrium for weak solutions of the spatially homogeneous Boltzmann Equation for soft potentials $(-4\le ...
B. Wennberg +32 more
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Statistical (T) rates of convergence
Glasnik Matematicki, 2004 A real lower triangular matrix \(T\) having nonnegative elements \( t(i,j)\) for which \(\{\sum t(i,j) \mid 0 N( \varepsilon )\) may of course be said to converge to \( L \). The convergence condition may be relaxed by stipulating that the points of exception to the inequality relationship should be sparse. \( K(x,L,\varepsilon| i) \) is the set of \(
Miller, H. I., Orhan, C.
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Tight Global Linear Convergence Rate Bounds for Douglas-Rachford Splitting
, 2017 Recently, several authors have shown local and global convergence rate results for Douglas-Rachford splitting under strong monotonicity, Lipschitz continuity, and cocoercivity assumptions. Most of these focus on the convex optimization setting.
Giselsson, Pontus
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Convergence Rate of Sieve Estimates
The Annals of Statistics, 1994 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shen, Xiaotong, Wong, Wing Hung
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Convergence of the empirical spectral measure of unitary Brownian motion [PDF]
, 2018 Let $\{U^N_t\}_{t\ge 0}$ be a standard Brownian motion on $\mathbb{U}(N)$. For fixed $N\in\mathbb{N}$ and $t>0$, we give explicit bounds on the $L_1$-Wasserstein distance of the empirical spectral measure of $U^N_t$ to both the ensemble-averaged spectral
Meckes, Elizabeth, Melcher, Tai
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$U$-Processes: Rates of Convergence
The Annals of Statistics, 1987 Let \(\xi_ 1,\xi_ 2,..\). be independent, identically distributed random variables and denote by \[ S_ n(f)=\sum_{1\leq i\neq j\leq n}f(\xi_ i,\xi_ j) \] the U-statistic with respect to the kernel f. The authors obtain almost sure convergence results for \(S_ n(f)\) uniformly over \(f\in F\) where F belongs to certain classes of kernels.
Nolan, Deborah, Pollard, David
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