Search results for "APPROXIMATION"

showing 10 items of 818 documents

Posterior moments and quantiles for the normal location model with Laplace prior

2021

We derive explicit expressions for arbitrary moments and quantiles of the posterior distribution of the location parameter η in the normal location model with Laplace prior, and use the results to approximate the posterior distribution of sums of independent copies of η.

Statistics and ProbabilityLaplace priorsLaplace priorLocation parameterreflected generalized gamma priorSettore SECS-P/05Posterior probability0211 other engineering and technologiesSettore SECS-P/05 - Econometria02 engineering and technology01 natural sciencesCornish-Fisher approximation010104 statistics & probabilityStatistics::Methodologyposterior quantile0101 mathematicsposterior moments and cumulantsMathematicsreflected generalized gamma priors021103 operations researchLaplace transformLocation modelMathematical analysisStatistics::Computationposterior moments and cumulantCornish–Fisher approximationSettore SECS-S/01 - StatisticaNormal location modelposterior quantilesQuantileCommunications in Statistics - Theory and Methods
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Quantile regression via iterative least squares computations

2012

We present an estimating framework for quantile regression where the usual L 1-norm objective function is replaced by its smooth parametric approximation. An exact path-following algorithm is derived, leading to the well-known ‘basic’ solutions interpolating exactly a number of observations equal to the number of parameters being estimated. We discuss briefly possible practical implications of the proposed approach, such as early stopping for large data sets, confidence intervals, and additional topics for future research.

Statistics and ProbabilityMathematical optimizationEarly stoppingquantile regressionsmooth approximationApplied MathematicsRegression analysisLeast squaresQuantile regressionleast squareModeling and SimulationNon-linear least squaresApplied mathematicsStatistics Probability and UncertaintyTotal least squaresSettore SECS-S/01 - StatisticaQuantileParametric statisticsMathematicsJournal of Statistical Computation and Simulation
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A generalization of the Binomial distribution based on the dependence ratio

2014

We propose a generalization of the Binomial distribution, called DR-Binomial, which accommodates dependence among units through a model based on the dependence ratio (Ekholm et al., Biometrika, 82, 1995, 847). Properties of the DR-Binomial are discussed, and the constraints on its parameter space are studied in detail. Likelihood-based inference is presented, using both the joint and profile likelihoods; the usefulness of the DR-Binomial in applications is illustrated on a real dataset displaying negative unit-dependence, and hence under-dispersion compared with the Binomial. Although the DR-Binomial turns out to be a reparameterization of Altham's Additive-Binomial and Kupper–Haseman's Cor…

Statistics and ProbabilityMathematics::Commutative AlgebraBinomial approximationNegative binomial distributionBinomial testNegative multinomial distributionBinomial distributionBeta-binomial distributionStatisticsApplied mathematicsMultinomial theoremMultinomial distributionStatistics Probability and UncertaintyMathematicsStatistica Neerlandica
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Mode-coupling theory for multiple decay channels

2013

We investigate the properties of a class of mode-coupling equations for the glass transition where the density mode decays into multiple relaxation channels. We prove the existence and uniqueness of the solutions for Newtonian as well as Brownian dynamics and demonstrate that they fulfill the requirements of correlation functions, in the latter case the solutions are purely relaxational. Furthermore, we construct an effective mode-coupling functional which allows to map the theory to the case of a single decay channel, such that the covariance principle found for the mode-coupling theory for simple liquids is properly generalized. This in turn allows establishing the maximum theorem stating…

Statistics and ProbabilityPhysicsClass (set theory)Statistical Mechanics (cond-mat.stat-mech)Maximum theoremFOS: Physical sciencesStatistical and Nonlinear PhysicsCovarianceCondensed Matter - Soft Condensed MatterSimple (abstract algebra)Mode couplingBrownian dynamicsSoft Condensed Matter (cond-mat.soft)Statistical physicsUniquenessRelaxation (approximation)Statistics Probability and UncertaintyCondensed Matter - Statistical Mechanics
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Cavity losses for the dissipative Jaynes–Cummings Hamiltonian beyond rotating wave approximation

2007

A microscopic derivation of the master equation for the Jaynes-Cummings model with cavity losses is given, taking into account the terms in the dissipator which vary with frequencies of the order of the vacuum Rabi frequency. Our approach allows to single out physical contexts wherein the usual phenomenological dissipator turns out to be fully justified and constitutes an extension of our previous analysis [Scala M. {\em et al.} 2007 Phys. Rev. A {\bf 75}, 013811], where a microscopic derivation was given in the framework of the Rotating Wave Approximation.

Statistics and ProbabilityPhysicsQuantum PhysicsGeneral Physics and AstronomyDissipatorFOS: Physical sciencesStatistical and Nonlinear Physics01 natural sciences010305 fluids & plasmassymbols.namesakeJaynes–Cummings modelModeling and SimulationQuantum mechanics0103 physical sciencesMaster equationsymbolsDissipative systemRotating wave approximation010306 general physicsHamiltonian (quantum mechanics)Quantum Physics (quant-ph)Mathematical PhysicsRabi frequency
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Non-Markovian dynamics of interacting qubit pair coupled to two independent bosonic baths

2009

The dynamics of two interacting spins coupled to separate bosonic baths is studied. An analytical solution in Born approximation for arbitrary spectral density functions of the bosonic environments is found. It is shown that in the non-Markovian cases concurrence "lives" longer or reaches greater values.

Statistics and ProbabilityPhysicsQuantum PhysicsSpinsnon-Markovian spin modelsDynamics (mechanics)FOS: Physical sciencesGeneral Physics and AstronomyMarkov processSpectral densityStatistical and Nonlinear PhysicsConcurrencesymbols.namesakeModeling and SimulationQubitQuantum mechanicssymbolsBorn approximationQuantum Physics (quant-ph)Mathematical Physics
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On an approximation problem for stochastic integrals where random time nets do not help

2006

Abstract Given a geometric Brownian motion S = ( S t ) t ∈ [ 0 , T ] and a Borel measurable function g : ( 0 , ∞ ) → R such that g ( S T ) ∈ L 2 , we approximate g ( S T ) - E g ( S T ) by ∑ i = 1 n v i - 1 ( S τ i - S τ i - 1 ) where 0 = τ 0 ⩽ ⋯ ⩽ τ n = T is an increasing sequence of stopping times and the v i - 1 are F τ i - 1 -measurable random variables such that E v i - 1 2 ( S τ i - S τ i - 1 ) 2 ∞ ( ( F t ) t ∈ [ 0 , T ] is the augmentation of the natural filtration of the underlying Brownian motion). In case that g is not almost surely linear, we show that one gets a lower bound for the L 2 -approximation rate of 1 / n if one optimizes over all nets consisting of n + 1 stopping time…

Statistics and ProbabilityRandom time netsMeasurable functionStochastic processStochastic integralsApplied MathematicsUpper and lower boundsNatural filtrationCombinatoricsModeling and SimulationStopping timeModelling and SimulationAlmost surelyApproximationBorel measureBrownian motionMathematicsStochastic Processes and their Applications
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On the stability and ergodicity of adaptive scaling Metropolis algorithms

2011

The stability and ergodicity properties of two adaptive random walk Metropolis algorithms are considered. The both algorithms adjust the scaling of the proposal distribution continuously based on the observed acceptance probability. Unlike the previously proposed forms of the algorithms, the adapted scaling parameter is not constrained within a predefined compact interval. The first algorithm is based on scale adaptation only, while the second one incorporates also covariance adaptation. A strong law of large numbers is shown to hold assuming that the target density is smooth enough and has either compact support or super-exponentially decaying tails.

Statistics and ProbabilityStochastic approximationMathematics - Statistics TheoryStatistics Theory (math.ST)Law of large numbersMultiple-try Metropolis01 natural sciencesStability (probability)010104 statistics & probabilityModelling and Simulation65C40 60J27 93E15 93E35Adaptive Markov chain Monte CarloFOS: Mathematics0101 mathematicsScalingMetropolis algorithmMathematicsta112Applied Mathematics010102 general mathematicsRejection samplingErgodicityProbability (math.PR)ta111CovarianceRandom walkMetropolis–Hastings algorithmModeling and SimulationAlgorithmStabilityMathematics - ProbabilityStochastic Processes and their Applications
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The coalescent in population models with time-inhomogeneous environment

2002

AbstractThe coalescent theory, well developed for the class of exchangeable population models with time-homogeneous reproduction law, is extended to a class of population models with time-inhomogeneous environment, where the population size is allowed to vary deterministically with time and where the distribution of the family sizes is allowed to change from generation to generation. A new class of time-inhomogeneous coalescent limit processes with simultaneous multiple mergers arises. Its distribution can be characterized in terms of product integrals.

Statistics and ProbabilityWeak convergencePopulation geneticsApplied MathematicsPopulation sizeVarying environmentPopulation geneticsProduct integralHeavy traffic approximationProduct integralStirling numbersCoalescent theoryFamily SizesDiffusion approximationPopulation modelAncestorsModelling and SimulationModeling and SimulationEconometricsQuantitative Biology::Populations and EvolutionCoalescentStatistical physicsWeak convergenceMathematicsStochastic Processes and their Applications
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Newton algorithm for Hamiltonian characterization in quantum control

2014

We propose a Newton algorithm to characterize the Hamiltonian of a quantum system interacting with a given laser field. The algorithm is based on the assumption that the evolution operator of the system is perfectly known at a fixed time. The computational scheme uses the Crank-Nicholson approximation to explicitly determine the derivatives of the propagator with respect to the Hamiltonians of the system. In order to globalize this algorithm, we use a continuation method that improves its convergence properties. This technique is applied to a two-level quantum system and to a molecular one with a double-well potential. The numerical tests show that accurate estimates of the unknown paramete…

Statistics and Probability[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC][ PHYS.QPHY ] Physics [physics]/Quantum Physics [quant-ph]Non uniquenessFOS: Physical sciencesGeneral Physics and AstronomyQuantum controlsymbols.namesake[PHYS.QPHY]Physics [physics]/Quantum Physics [quant-ph]Fixed time[ CHIM.OTHE ] Chemical Sciences/OtherQuantum systemNumerical testsMathematical PhysicsMathematicsQuantum PhysicsPropagatorStatistical and Nonlinear PhysicsNMRContinuation methodModeling and Simulationsymbolsinverse problemidentification02.30.Yy Control theory02.30.Tb Operator theory42.50.Ct Quantum description of interaction of light and matter; related experiments02.60.Cb Numerical simulation; solution of equations03.65.Ge Solutions of wave equations: bound states02.30.Mv Approximations and expansions[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Quantum Physics (quant-ph)Hamiltonian (quantum mechanics)[CHIM.OTHE]Chemical Sciences/OtherAlgorithmcontrol
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