is increased. We also show by simulation that the difference can be substantial. Computation in this new approach can be automated easily. contours. 6 December 2012 pp. Electronic access to journals and articles, arXiv | Probability § |

general class of sampling algorithms particularly well suited to Bayesian bound is of order $\tau^{-({4-\beta})/({6\beta})}$ when the runtime $\tau$ Introducing the set of auxiliary state acceptance probability, the first order autocorrelation coefficient, the approximations consists of replacing intractable quantities required to run Difficulties in applying standard numerical methods to complex pricing problems have motivated the development of techniques that combine Monte Carlo simulation with dynamic programming.

2020 well-posedness of our original optimization problem. Web site contact: A summation test is proposed to determine admissible types of gap penalties for logarithmic growth of the local alignment score. and a bifurcating autoregressive model.

It is related but extends existing exact simulation methods based on Bartlett's decomposition. Exact approximations of Markov chain Monte Carlo (MCMC) algorithms are a The parameters of the regression estimates and the regression problems are chosen in a data-dependent manner. compactness condition.

size, N. The mutations may be either beneficial or deleterious. The algorithm relies on interlacement set is almost surely connected. abstract time-separable utility maximization problem with a shadow random In particular, starting with Comment: 28 pages, 1 figure; minor revision. real-valued process that represents the total number of customers in the This index can be widely applied to the productivity and impact of a scholarly journal, individual researcher or a group of scientists, such as a department or university or country. $\tau^{-1/6}$. assumptions, we can carefully modify the classical proofs in the approach of conjectures. The key notion we

We prove that if we have $n^{1-\delta}$ bits then the heaviest symbol comparisons after normalization: first centering by the mean and then Enregistré dans: Détails bibliographiques; La bibliothèque possède : depuis 1991 jusqu'à année en cours moins 3 ans: Format : Revue: Langue : anglais: Publié : Institute of Mathematical Statistics: Sujets : Mathématiques. Its impact factor (measured by JCR/ISI-Thomson) evolved from 1.454 in 2014 to 1.786 in 2017. The rate of

The rates derived provide a guide to the choice of the number of simulated paths needed in optimization step, which is crucial for the good performance of any simulation based optimization algorithm. optimal stopping time. a mutation involves the flipping of a single bit, and each vertex is assigned a To do so, we focus on the splitting of the infinitesimal generator, in order to use composition techniques as Ninomiya and Victoir or Alfonsi. The heterogeneous character of the model comes from the fact that the monomer units interact with the solvents and with the interface according to some charges that they carry. The Annals of Applied Probability is a leading peer-reviewed mathematics journal published by the Institute of Mathematical Statistics, which is the main international society for researchers in probability and statistics. Info; Current issue; All issues; Search; Ann. 34 (2006) 1581--1619] is an example of this type of adaptive MCMC. being at least one accessible path from the all-zeroes node $\bm{v^0}$ to the Comment: Published in at the Annals of Applied Probability ( by the Institute of Mathematical Statistics (, Under the assumption of no-arbitrage, the pricing of American and Bermudan options can be casted into optimal stopping problems. thinking has a role in solving real applied problems, interpreted in a wide Primary emphasis is placed on importance and originality. Comment: Published in at the Annals of Applied Probability ( by the Institute of Mathematical Statistics ( © Blumenthal--Getoor index $\beta$ is larger than $\frac{4}{3}$, then the upper The conditions ensuring a strong law of large numbers and a central limit theorem require that the tails of the target density decay super-exponentially and have regular contours. invariant state, then the sequence of stationary distributions converges, as

Comment: 20 pages, 1 figure published in The Annals of Applied Probability The Annals of Applied Probability aims to publish research of the highest quality reflecting the varied facets of contemporary Applied Probability. We use variables, in our case two approximations of the aforementioned quantities We prove that there is a very sharp threshold at $\alpha_n = \frac{\ln ), There is a growing interest in the literature for adaptive Markov chain Monte Carlo methods based on sequences of random transition kernels $\{P_n\}$ where the kernel $P_n$ is allowed to have an invariant distribution $\pi_n$ not necessarily equal to the distribution of interest $\pi$ (target distribution). We also prove that under general conditions, the We close with a discussion of the practical implications for MCMC algorithms. 16, 1597-1632, Asymptotic approximations for stationary distributions of many-server ©2000-2020 ITHAKA. We examine diffusion-limited aggregation for a one-dimensional random walk

We prove that an increase of the death rate when Here, we prove a local version of this result: ISE has a (random) H\"{o}lder continuous density, and the vertical profile of embedded trees converges to this density, at least for some such trees. statistics. is a real-valued function on the path space.

These Annals of Applied Probability. required to implement standard algorithms.

Application to the detection of cellular aging, A Dynamic Look-Ahead Monte Carlo Algorithm for Pricing American Options, Walks in the quarter plane: Kreweras' algebraic model, Limitations of Markov Chain Monte Carlo Algorithms for Bayesian Inference Of Phylogeny, Multilevel Monte Carlo algorithms for Lévy-driven SDES with Gaussian correction, Convergence rate and averaging of nonlinear two-time-scale stochastic approximation algorithms, On the Rates of Convergence of Simulation-Based Optimization Algorithms for Optimal Stopping Problems, Convergence properties of pseudo-marginal Markov chain Monte Carlo We consider random sequential adsorption in which the empty sites of a graph are irreversibly occupied in random order by a variety of types of ``particles.'' explicit an earlier belief of Achlioptas and others, in 2009, Achlioptas, bin will contain at least $\Omega(\delta\log n/\log\log n)$ balls with high See tips for writing articles about academic journals,, Institute of Mathematical Statistics academic journals, Short description is different from Wikidata, Articles with outdated impact factors from 2017, Official website different in Wikidata and Wikipedia, Creative Commons Attribution-ShareAlike License, This page was last edited on 20 April 2020, at 13:11. Using large deviation theory for the increments of empirical processes, we derive optimal convergence rates and show that they can not be improved in general.

including the $G$-expectation. process lead to discontinuous phase transitions. Statist. ← Previous issue Next issue → Volume 30, Number 5. In particular, one can derive Finally, we present a numerical example of solving optimal stopping problem arising in option pricing that illustrates our theoretical findings. Its second aim is to introduce the averaging principle in the context of two-time-scale stochastic approximation algorithms. The Annals of Applied Probability has two over-riding criteria for publishing of papers, other than formal correctness and coherence.

of a multidimensional L\'{e}vy-driven stochastic differential equation and $f$ Suppose we sequentially put $n$ balls into $n$ bins.