Search results for "Exponent"

showing 10 items of 896 documents

Cross Correlations in Scaling Analyses of Phase Transitions

2008

Thermal or finite-size scaling analyses of importance sampling Monte Carlo time series in the vicinity of phase transition points often combine different estimates for the same quantity, such as a critical exponent, with the intent to reduce statistical fluctuations. We point out that the origin of such estimates in the same time series results in often pronounced cross-correlations which are usually ignored even in high-precision studies, generically leading to significant underestimation of statistical fluctuations. We suggest to use a simple extension of the conventional analysis taking correlation effects into account, which leads to improved estimators with often substantially reduced …

Statistical Mechanics (cond-mat.stat-mech)Monte Carlo methodFOS: Physical sciencesGeneral Physics and AstronomyStatistical fluctuationsDynamic Monte Carlo methodMonte Carlo method in statistical physicsStatistical physicsCritical exponentScalingCondensed Matter - Statistical MechanicsImportance samplingMonte Carlo molecular modelingMathematicsPhysical Review Letters
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Finite-size scaling analysis of the ?4 field theory on the square lattice

1986

Monte-Carlo calculations are performed for the model Hamiltonian ℋ = ∑i[(r/2)Φ 2(i)+(u/4)/gF4(i)]+∑ (C/2)[Φ (i)−Φ(j)]2 for various values of the parametersr, u, C in the crossover region from the Ising limit (r→-∞,u+∞) to the displacive limit (r=0). The variableφ(i) is a scalar continuous spin variable which can lie in the range-∞<φ(i)<+∞, for each lattice site (i).φ(i) is a priori selected proportional to the single-site probability in our Monte Carlo algorithm. The critical line is obtained in very good agreement with other previous approaches. A decrease of apparent critical exponents, deduced from a finite-size scaling analysis, is attributed to a crossover toward mean-field values at t…

Statistical and Nonlinear PhysicsSquare latticesymbols.namesakeMean field theoryCritical lineQuantum mechanicsLattice (order)symbolsIsing modelHamiltonian (quantum mechanics)Critical exponentScalingMathematical PhysicsMathematicsJournal of Statistical Physics
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Forecasting time series with missing data using Holt's model

2009

This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.

Statistics and ProbabilityApplied MathematicsAutocorrelationExponential smoothingLinear modelData transformation (statistics)EstimatorMissing dataExpectation–maximization algorithmStatisticsStatistics Probability and UncertaintyAdditive modelAlgorithmMathematicsJournal of Statistical Planning and Inference
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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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System size dependence of the autocorrelation time for the Swendsen-Wang Ising model

1990

Abstract We present Monte Carlo simulation results of the autocorrelation time for the Swendsen-Wang method for the simulation of the Ising model. We have calculated the exponential and the integrated autocorrelation time at the critical point T c of the two-dimensional Ising model. Our results indicate that both autocorrelation times depend logarithmically on the linear system size L instead of a power law. The simulations were carried out on the parallel computer of the condensed matter theory group at the University of Mainz.

Statistics and ProbabilityComputer simulationCritical point (thermodynamics)AutocorrelationMonte Carlo methodSquare-lattice Ising modelIsing modelStatistical physicsCondensed Matter PhysicsPower lawMathematicsExponential functionPhysica A: Statistical Mechanics and its Applications
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The angle of repose of spherical grains in granular Hele-Shaw cells: A molecular dynamics study

2007

We report the results of three dimensional molecular dynamic simulations on the angle of repose of a sandpile formed by pouring mono-sized cohesionless spherical grains into a granular Hele-Shaw cell. In particular, we are interested to investigate the effects of those variables which may impact significantly on pattern formation of granular mixtures in Hele-Shaw cells. The results indicate that the frictional forces influence remarkably the formation of pile on the grain level. Furthermore, We see that increasing grain insertion rate decreases slightly the angle of repose. We also find that in accordance with experimental results, the cell thickness is another significant factor and the an…

Statistics and ProbabilityCondensed Matter - Materials ScienceMaterials scienceStatistical Mechanics (cond-mat.stat-mech)Pattern formationMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesfood and beveragesStatistical and Nonlinear PhysicsFunction (mathematics)MechanicsAngle of reposeMolecular dynamicsGranular matterStatistics Probability and UncertaintyExponential decayCondensed Matter - Statistical Mechanics
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Kinetics of domain growth in finite Ising strips

1992

Abstract Monte Carlo simulations are presented for the kinetics of ordering of the two-dimensional nearest-neighbor Ising models in an L x M geometry with two free boundaries of length M ⪢ L . This geometry models a “terrace” of width L on regularly stepped surfaces, adatoms adsorbed on neighboring terraces being assumed to be noninteracting. Starting out with an initially random configuration of the atoms in the lattice gas at coverage θ = 1 2 in the square lattice, quenching experiments to temperatures in the range 0.85⩽ T / T c ⩽1 are considered, assuming a dynamics of the Glauber model type (no conservation laws being operative). At T c the ordering behavior can be described in terms of…

Statistics and ProbabilityConservation lawCorrelation function (statistical mechanics)Condensed matter physicsLattice (order)Monte Carlo methodExponentIsing modelCondensed Matter PhysicsSquare latticeGlauberMathematicsPhysica A: Statistical Mechanics and its Applications
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Large deviations results for subexponential tails, with applications to insurance risk

1996

AbstractConsider a random walk or Lévy process {St} and let τ(u) = inf {t⩾0 : St > u}, P(u)(·) = P(· | τ(u) < ∞). Assuming that the upwards jumps are heavy-tailed, say subexponential (e.g. Pareto, Weibull or lognormal), the asymptotic form of the P(u)-distribution of the process {St} up to time τ(u) is described as u → ∞. Essentially, the results confirm the folklore that level crossing occurs as result of one big jump. Particular sharp conclusions are obtained for downwards skip-free processes like the classical compound Poisson insurance risk process where the formulation is in terms of total variation convergence. The ideas of the proof involve excursions and path decompositions for Mark…

Statistics and ProbabilityExponential distributionRegular variationRuin probabilityExcursionRandom walkDownwards skip-free processLévy processConditioned limit theoremTotal variation convergenceCombinatoricsInsurance riskPath decompositionIntegrated tailProbability theoryModelling and SimulationExtreme value theoryMaximum domain of attractionMathematicsStochastic processApplied MathematicsExtreme value theoryRandom walkSubexponential distributionModeling and SimulationLog-normal distributionLarge deviations theory60K1060F10Stochastic Processes and their Applications
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A Software Tool for the Exponential Power Distribution: The normalp Package

2005

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo-random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studi…

Statistics and ProbabilityExponential distributionTheoretical computer scienceComputer scienceAsymptotic distributionDistribution fittingLaplace distributionExponential familyGamma distributionStatistics Probability and UncertaintyNatural exponential familyProbability integral transformAlgorithmlcsh:Statisticslcsh:HA1-4737exponential power distribution R estimation linear regressionSoftwareJournal of Statistical Software
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Holt–Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data

2007

Abstract This paper provides a formulation for the additive Holt–Winters forecasting procedure that simplifies both obtaining maximum likelihood estimates of all unknowns, smoothing parameters and initial conditions, and the computation of point forecasts and reliable predictive intervals. The stochastic component of the model is introduced by means of additive, uncorrelated, homoscedastic and Normal errors, and then the joint distribution of the data vector, a multivariate Normal distribution, is obtained. In the case where a data transformation was used to improve the fit of the model, cumulative forecasts are obtained here using a Monte-Carlo approximation. This paper describes the metho…

Statistics and ProbabilityExponential smoothingData transformation (statistics)Prediction intervalMultivariate normal distributionJoint probability distributionHomoscedasticityStatisticsEconometricsStatistics Probability and UncertaintyTime seriesPhysics::Atmospheric and Oceanic PhysicsSmoothingMathematicsJournal of Applied Statistics
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