Search results for "prose"

showing 10 items of 651 documents

Journalistisen työprosessin jäljillä

2017

Social sciences (General)H1-99Communication. Mass mediajournalismitoimitustyöjournalistiikkaKeskusteluatyöprosessittoimittajatP87-96Journalism. The periodical press etc.PN4699-5650Media & viestintä
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Finite-size effects in dynamics of zero-range processes

2010

The finite-size effects prominent in zero-range processes exhibiting a condensation transition are studied by using continuous-time Monte Carlo simulations. We observe that, well above the thermodynamic critical point, both static and dynamic properties display fluid-like behavior up to a density {\rho}c (L), which is the finite-size counterpart of the critical density {\rho}c = {\rho}c (L \rightarrow \infty). We determine this density from the cross-over behavior of the average size of the largest cluster. We then show that several dynamical characteristics undergo a qualitative change at this density. In particular, the size distribution of the largest cluster at the moment of relocation,…

Statistical Mechanics (cond-mat.stat-mech)Stochastic processCrossoverMonte Carlo methodFOS: Physical sciencesMonihiukkasmallitfaasimuutoksetMany-particle modelsphase transitionsAverage sizeCritical point (thermodynamics)transport theorykuljetusteoriaStatistical physicsCondensed Matter - Statistical MechanicsMathematicsstokastiset prosessit
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Conditional convex orders and measurable martingale couplings

2014

Strassen's classical martingale coupling theorem states that two real-valued random variables are ordered in the convex (resp.\ increasing convex) stochastic order if and only if they admit a martingale (resp.\ submartingale) coupling. By analyzing topological properties of spaces of probability measures equipped with a Wasserstein metric and applying a measurable selection theorem, we prove a conditional version of this result for real-valued random variables conditioned on a random element taking values in a general measurable space. We also provide an analogue of the conditional martingale coupling theorem in the language of probability kernels and illustrate how this result can be appli…

Statistics and Probability01 natural sciencesStochastic ordering010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityStrassen algorithmWasserstein metricmartingale couplingvektorit (matematiikka)FOS: MathematicsApplied mathematics0101 mathematicsstokastiset prosessitMathematicsProbability measurekytkentäconvex stochastic ordermatematiikka010102 general mathematicsProbability (math.PR)Random elementMarkov chain Monte Carloconditional couplingincreasing convex stochastic orderpointwise couplingsymbols60E15probability kernelMartingale (probability theory)Random variableMathematics - Probability
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Weighted bounded mean oscillation applied to backward stochastic differential equations

2015

Abstract We deduce conditional L p -estimates for the variation of a solution of a BSDE. Both quadratic and sub-quadratic types of BSDEs are considered, and using the theory of weighted bounded mean oscillation we deduce new tail estimates for the solution ( Y , Z ) on subintervals of [ 0 , T ] . Some new results for the decoupling technique introduced in Geiss and Ylinen (2019) are obtained as well and some applications of the tail estimates are given.

Statistics and ProbabilityApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysis01 natural sciencesBSDEsBounded mean oscillationdecoupling010104 statistics & probabilityStochastic differential equationvärähtelytQuadratic equationJohn-Nirenberg theoremtail estimatesModeling and Simulation60H10 60G99FOS: MathematicsDecoupling (probability)weighted bounded mean oscillation0101 mathematicsdifferentiaaliyhtälötMathematics - Probabilitystokastiset prosessitMathematicsStochastic Processes and their Applications
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Time-dependent weak rate of convergence for functions of generalized bounded variation

2016

Let $W$ denote the Brownian motion. For any exponentially bounded Borel function $g$ the function $u$ defined by $u(t,x)= \mathbb{E}[g(x{+}\sigma W_{T-t})]$ is the stochastic solution of the backward heat equation with terminal condition $g$. Let $u^n(t,x)$ denote the corresponding approximation generated by a simple symmetric random walk with time steps $2T/n$ and space steps $\pm \sigma \sqrt{T/n}$ where $\sigma > 0$. For quite irregular terminal conditions $g$ (bounded variation on compact intervals, locally H\"older continuous) the rate of convergence of $u^n(t,x)$ to $u(t,x)$ is considered, and also the behavior of the error $u^n(t,x)-u(t,x)$ as $t$ tends to $T$

Statistics and ProbabilityApproximation using simple random walkweak rate of convergence01 natural sciencesStochastic solution41A25 65M15 (Primary) 35K05 60G50 (Secondary)010104 statistics & probabilityExponential growthFOS: Mathematics0101 mathematicsBrownian motionstokastiset prosessitMathematicsosittaisdifferentiaaliyhtälötApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysisfinite difference approximation of the heat equationFunction (mathematics)Rate of convergenceBounded functionBounded variationnumeerinen analyysiapproksimointiStatistics Probability and UncertaintyMathematics - ProbabilityStochastic Analysis and Applications
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Mean square rate of convergence for random walk approximation of forward-backward SDEs

2020

AbstractLet (Y,Z) denote the solution to a forward-backward stochastic differential equation (FBSDE). If one constructs a random walk$B^n$from the underlying Brownian motionBby Skorokhod embedding, one can show$L_2$-convergence of the corresponding solutions$(Y^n,Z^n)$to$(Y, Z).$We estimate the rate of convergence based on smoothness properties, especially for a terminal condition function in$C^{2,\alpha}$. The proof relies on an approximative representation of$Z^n$and uses the concept of discretized Malliavin calculus. Moreover, we use growth and smoothness properties of the partial differential equation associated to the FBSDE, as well as of the finite difference equations associated to t…

Statistics and ProbabilityDiscretizationapproximation schemeMalliavin calculus01 natural sciences010104 statistics & probabilityconvergence rateMathematics::ProbabilityConvergence (routing)random walk approximation 2010 Mathematics Subject Classification: Primary 60H10FOS: MathematicsApplied mathematics0101 mathematicsBrownian motionrandom walk approximationMathematicsstokastiset prosessitSmoothness (probability theory)konvergenssiApplied Mathematics010102 general mathematicsProbability (math.PR)Backward stochastic differential equationsFunction (mathematics)Random walkfinite difference equation[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Rate of convergencebackward stochastic differential equations60G50 Secondary 60H3060H35approksimointidifferentiaaliyhtälötMathematics - Probability
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Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

2017

We establish an ordering criterion for the asymptotic variances of two consistent Markov chain Monte Carlo (MCMC) estimators: an importance sampling (IS) estimator, based on an approximate reversible chain and subsequent IS weighting, and a standard MCMC estimator, based on an exact reversible chain. Essentially, we relax the criterion of the Peskun type covariance ordering by considering two different invariant probabilities, and obtain, in place of a strict ordering of asymptotic variances, a bound of the asymptotic variance of IS by that of the direct MCMC. Simple examples show that IS can have arbitrarily better or worse asymptotic variance than Metropolis-Hastings and delayed-acceptanc…

Statistics and ProbabilityFOS: Computer and information sciencesdelayed-acceptanceMarkovin ketjut01 natural sciencesStatistics - Computationasymptotic variance010104 statistics & probabilitysymbols.namesake60J22 65C05unbiased estimatorFOS: MathematicsApplied mathematics0101 mathematicsComputation (stat.CO)stokastiset prosessitestimointiMathematicsnumeeriset menetelmätpseudo-marginal algorithmApplied Mathematics010102 general mathematicsProbability (math.PR)EstimatorMarkov chain Monte CarloCovarianceInfimum and supremumWeightingMarkov chain Monte CarloMonte Carlo -menetelmätDelta methodimportance samplingModeling and SimulationBounded functionsymbolsImportance samplingMathematics - Probability
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Uniform measure density condition and game regularity for tug-of-war games

2018

We show that a uniform measure density condition implies game regularity for all 2 < p < ∞ in a stochastic game called “tug-of-war with noise”. The proof utilizes suitable choices of strategies combined with estimates for the associated stopping times and density estimates for the sum of independent and identically distributed random vectors. peerReviewed

Statistics and ProbabilityIndependent and identically distributed random variablesComputer Science::Computer Science and Game Theorygame regularitydensity estimate for the sum of i.i.d. random vectorsTug of war01 natural sciencesMeasure (mathematics)$p$-regularityMathematics - Analysis of PDEsFOS: MathematicsApplied mathematicspeliteoriastochastic games0101 mathematics91A15 60G50 35J92Mathematicsp-harmonic functionsstokastiset prosessit$p$-harmonic functionsosittaisdifferentiaaliyhtälöthitting probability010102 general mathematicsStochastic gametug-of-war gamesProbability (math.PR)uniform measure density condition010101 applied mathematicsNoiseuniform distribution in a ballMathematics - ProbabilityAnalysis of PDEs (math.AP)
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On decoupling in Banach spaces

2021

AbstractWe consider decoupling inequalities for random variables taking values in a Banach space X. We restrict the class of distributions that appear as conditional distributions while decoupling and show that each adapted process can be approximated by a Haar-type expansion in which only the pre-specified conditional distributions appear. Moreover, we show that in our framework a progressive enlargement of the underlying filtration does not affect the decoupling properties (in particular, it does not affect the constants involved). As a special case, we deal with one-sided moment inequalities for decoupled dyadic (i.e., Paley–Walsh) martingales and show that Burkholder–Davis–Gundy-type in…

Statistics and ProbabilityPure mathematicsGeneral MathematicsBanach space01 natural sciences010104 statistics & probabilityFOS: MathematicsFiltration (mathematics)decoupling in Banach spaces0101 mathematicsSpecial casestokastiset prosessitMathematicsMathematics::Functional Analysisdyadic martingalesProbability (math.PR)010102 general mathematicsDecoupling (cosmology)Conditional probability distributionBanachin avaruudetAdapted processMoment (mathematics)regular conditional probabilities60E15 60H05 46B09stochastic integrationStatistics Probability and UncertaintyfunktionaalianalyysiRandom variableMathematics - Probability
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Donsker-Type Theorem for BSDEs: Rate of Convergence

2019

In this paper, we study in the Markovian case the rate of convergence in Wasserstein distance when the solution to a BSDE is approximated by a solution to a BSDE driven by a scaled random walk as introduced in Briand, Delyon and Mémin (Electron. Commun. Probab. 6 (2001) Art. ID 1). This is related to the approximation of solutions to semilinear second order parabolic PDEs by solutions to their associated finite difference schemes and the speed of convergence. peerReviewed

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Markov processType (model theory)scaled random walk01 natural sciencesconvergence rate010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityConvergence (routing)FOS: MathematicsOrder (group theory)Applied mathematicsWasserstein distance0101 mathematicsDonsker's theoremstokastiset prosessitMathematicskonvergenssiProbability (math.PR)010102 general mathematicsFinite differenceRandom walk[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Rate of convergencebackward stochastic differential equationssymbolsapproksimointiDonsker’s theoremfinite difference schemedifferentiaaliyhtälötMathematics - Probability
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