Search results for "Smooth"

showing 10 items of 710 documents

Estimates of maximal functions measuring local smoothness

1999

Letη be a nondecreasing function on (0, 1] such thatη(t)/t decreases andη(+0)=0. Letf ∈L(I n ) (I≡[0,1]. Set $${\mathcal{N}}_\eta f(x) = \sup \frac{1}{{\left| Q \right|\eta (\left| Q \right|^{1/n} )}} \smallint _Q \left| {f(t) - f(x)} \right|dt,$$ , where the supremum is taken over all cubes containing the pointx. Forη=t α (0<α≤1) this definition was given by A.Calderon. In the paper we prove estimates of the maximal functions $${\mathcal{N}}_\eta f$$ , along with some embedding theorems. In particular, we prove the following Sobolev type inequality: if $$1 \leqslant p< q< \infty , \theta \equiv n(1/p - 1/q)< 1, and \eta (t) \leqslant t^\theta \sigma (t),$$ , then $$\parallel {\mathcal{N}}_…

Sobolev spaceDiscrete mathematicsSmoothness (probability theory)General MathematicsMaximal functionType inequalityModulus of continuityMathematicsAnalysis Mathematica
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SIOPRED performance in a Forecasting Blind Competition

2012

In this paper we present the results obtained by applying our automatic forecasting support system, named SIOPRED, over a data set of time series in a Forecasting Blind Competition. In order to apply our procedure for providing point forecasts it has been necessary to develop an interactive strategy for the choice of the suitable length of the seasonal cycle and the seasonality form for a generalized exponential smoothing method, which have been obtained using SIOPRED. For the choice of those essential characteristics of forecasting methods, also a certain multi-objective formulation which minimizes several measures of fitting is used. Once these specifications are established, the model pa…

Soft computingData setCompetition (economics)Mathematical optimizationSeries (mathematics)Computer scienceExponential smoothingPoint (geometry)Physics::Atmospheric and Oceanic PhysicsSmoothingNonlinear programming2012 IEEE Conference on Evolving and Adaptive Intelligent Systems
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Surface soil water content estimation based on thermal inertia and Bayesian smoothing

2014

Soil water content plays a critical role in agro-hydrology since it regulates the rainfall partition between surface runoff and infiltration and, the energy partition between sensible and latent heat fluxes. Current thermal inertia models characterize the spatial and temporal variability of water content by assuming a sinusoidal behavior of the land surface temperature between subsequent acquisitions. Such behavior implicitly supposes clear sky during the whole interval between the thermal acquisitions; but, since this assumption is not necessarily verified even if sky is clear at the exact epoch of acquisition, , the accuracy of the model may be questioned due to spatial and temporal varia…

Soil Water Content Bayesian Smoothing Thermal Inertia MODIS SEVIRI.Meteorologymedia_common.quotation_subjectPolar orbitBayesian SmoothingLatent heatSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliElectrical and Electronic EngineeringWater contentImage resolutionRemote sensingmedia_commonSettore ING-INF/03 - TelecomunicazioniElectronic Optical and Magnetic MaterialSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaThermal InertiaComputer Science Applications1707 Computer Vision and Pattern RecognitionSEVIRICondensed Matter PhysicsApplied MathematicGeographyMODISSoil Water ContentSkyGeostationary orbitSurface runoffShortwaveSettore ICAR/06 - Topografia E CartografiaSPIE Proceedings
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First Experiences on an Accurate SPH Method on GPUs

2017

It is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.

SpeedupExploitGPUsComputer scienceComputer Networks and CommunicationsGPUSmoothed Particle Hydrodynamics method010103 numerical & computational mathematics01 natural sciencesComputational scienceSmoothed-particle hydrodynamicsInstruction setSettore MAT/08 - Analisi NumericaArtificial IntelligenceAccuracy; Approximation; GPUs; Kernel function; Smoothed particle hydrodynamics method; Speed-Up; Artificial Intelligence; Computer Networks and Communications; 1707; Signal Processing0101 mathematicsApproximationAccuracy1707Random access memoryLinear systemKernel functionSpeed-Up010101 applied mathematicsKernel (statistics)Signal Processing
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Quasi-interpolating and Smoothing Local Splines

2015

In this chapter, local quasi-interpolating and smoothing splines are described. Although approximation properties of local spline are similar to properties of the global interpolating and smoothing splines, their design does not require the IIR filtering of the whole data array. The computation of a local spline value at some point utilizes only a few adjacent grid samples. Therefore, local splines can be used for real-time processing of signals and for the design of FIR filter banks generating wavelets and wavelet frames (Chaps. 12 and 14). In the chapter, local splines of different orders are designed and their approximation properties are established which are compared with the propertie…

Spline (mathematics)Smoothing splineComputer Science::GraphicsWaveletFinite impulse responseComputer scienceApproximation propertyComputationApplied mathematicsArray data typeSmoothingMathematics::Numerical Analysis
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$L_2$-variation of L\'{e}vy driven BSDEs with non-smooth terminal conditions

2016

We consider the $L_2$-regularity of solutions to backward stochastic differential equations (BSDEs) with Lipschitz generators driven by a Brownian motion and a Poisson random measure associated with a L\'{e}vy process $(X_t)_{t\in[0,T]}$. The terminal condition may be a Borel function of finitely many increments of the L\'{e}vy process which is not necessarily Lipschitz but only satisfies a fractional smoothness condition. The results are obtained by investigating how the special structure appearing in the chaos expansion of the terminal condition is inherited by the solution to the BSDE.

Statistics and Probability$L_{2}$-regularityPure mathematicsSmoothness (probability theory)Malliavin calculus010102 general mathematicsChaos expansionPoisson random measureFunction (mathematics)Lipschitz continuityMalliavin calculus01 natural sciencesLévy process010104 statistics & probabilityStochastic differential equationMathematics::ProbabilityLévy processesbackward stochastic differential equations0101 mathematicsL 2 -regularityBrownian motionMathematics - ProbabilityMathematics
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Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach

2017

Summary This paper is concerned with interval estimation for the breakpoint parameter in segmented regression. We present score-type confidence intervals derived from the score statistic itself and from the recently proposed gradient statistic. Due to lack of regularity conditions of the score, non-smoothness and non-monotonicity, naive application of the score-based statistics is unfeasible and we propose to exploit the smoothed score obtained via induced smoothing. We compare our proposals with the traditional methods based on the Wald and the likelihood ratio statistics via simulations and an analysis of a real dataset: results show that the smoothed score-like statistics perform in prac…

Statistics and Probability010504 meteorology & atmospheric sciencesInterval estimationBreakpointinduced smoothingScore01 natural sciencesConfidence intervalchangepoint010104 statistics & probabilitypiecewise linear relationshipconfidence intervalscore inferenceStatistics0101 mathematicsStatistics Probability and UncertaintySegmented regressionSettore SECS-S/01 - StatisticaStatisticSmoothing0105 earth and related environmental sciencesMathematicsAustralian &amp; New Zealand Journal of Statistics
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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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Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity

2014

Recent development of intensity estimation for inhomogeneous spatial point processes with covariates suggests that kerneling in the covariate space is a competitive intensity estimation method for inhomogeneous Poisson processes. It is not known whether this advantageous performance is still valid when the points interact. In the simplest common case, this happens, for example, when the objects presented as points have a spatial dimension. In this paper, kerneling in the covariate space is extended to Gibbs processes with covariates-dependent chemical activity and inhibitive interactions, and the performance of the approach is studied through extensive simulation experiments. It is demonstr…

Statistics and ProbabilityDimensionality reductionNonparametric statisticsPoisson distributionPoint processsymbols.namesakeDimension (vector space)CovariatesymbolsEconometricsStatistics::MethodologyStatistical physicsStatistics Probability and UncertaintySmoothingMathematicsParametric statisticsStatistica Neerlandica
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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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