Search results for "Random"

showing 10 items of 3931 documents

Long-term experiments and strip plot designs

2015

In a long-term experiment usually the experimenter needs to know whether the effect of a treatment varies over time. But time usually has both a fixed and a random effects over the output and the difficulty in the analysis depends on the particular design considered and the availability of covariates. Actually, as shown in the paper, the presence of covariates can be very useful to model the random effect of time. In this paper a model to analyze data from a long-term strip plot design with covariates is proposed. Its effectiveness will be tested using both simulated and real data from a crop rotation experiment.

Statistics and ProbabilitySettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaRandom effects modelPlot (graphics)Experimental designTerm (time)Repeated measureStatisticsCovariateEconometricsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaCovariatesMathematics
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A note on Malliavin smoothness on the Lévy space

2017

We consider Malliavin calculus based on the Itô chaos decomposition of square integrable random variables on the Lévy space. We show that when a random variable satisfies a certain measurability condition, its differentiability and fractional differentiability can be determined by weighted Lebesgue spaces. The measurability condition is satisfied for all random variables if the underlying Lévy process is a compound Poisson process on a finite time interval. peerReviewed

Statistics and ProbabilitySmoothness (probability theory)matematiikkaLévy processMalliavin calculus010102 general mathematicsMalliavin calculus01 natural sciencesLévy processinterpolation010104 statistics & probability60H07Mathematics::ProbabilitySquare-integrable functionCompound Poisson processApplied mathematicsinterpolointiDifferentiable functiontila0101 mathematicsStatistics Probability and UncertaintyLp spaceRandom variable60G51MathematicsElectronic Communications in Probability
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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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Test and power considerations for multiple endpoint analyses using sequentially rejective graphical procedures

2009

A variety of powerful test procedures are available for the analysis of clinical trials addressing multiple objectives, such as comparing several treatments with a control, assessing the benefit of a new drug for more than one endpoint, etc. However, some of these procedures have reached a level of complexity that makes it difficult to communicate the underlying test strategies to clinical teams. Graphical approaches have been proposed instead that facilitate the derivation and communication of Bonferroni-based closed test procedures. In this paper we give a coherent description of the methodology and illustrate it with a real clinical trial example. We further discuss suitable power measur…

Statistics and ProbabilityTest strategyEndpoint DeterminationEpidemiologyComputer scienceControl (management)Analysis of clinical trialsMachine learningcomputer.software_genresymbols.namesakeDrug TherapyComputer GraphicsConfidence IntervalsHumansMulticenter Studies as TopicRandomized Controlled Trials as Topicbusiness.industryVariety (cybernetics)Test (assessment)Clinical trialBonferroni correctionClinical Trials Phase III as TopicData Interpretation StatisticalMultiple comparisons problemsymbolsArtificial intelligencebusinessAlgorithmcomputerStatistics in Medicine
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Sample size in cluster-randomized trials with time to event as the primary endpoint

2011

In cluster-randomized trials, groups of individuals (clusters) are randomized to the treatments or interventions to be compared. In many of those trials, the primary objective is to compare the time for an event to occur between randomized groups, and the shared frailty model well fits clustered time-to-event data. Members of the same cluster tend to be more similar than members of different clusters, causing correlations. As correlations affect the power of a trial to detect intervention effects, the clustered design has to be considered in planning the sample size. In this publication, we derive a sample size formula for clustered time-to-event data with constant marginal baseline hazards…

Statistics and ProbabilityTime FactorsEndpoint DeterminationSubstance-Related DisordersEpidemiologyPsychological interventionBiostatisticsTime-to-Treatmentlaw.inventionCorrelationRandom AllocationRandomized controlled triallawStatisticsClinical endpointEconometricsCluster AnalysisHumansPoisson DistributionBaseline (configuration management)Randomized Controlled Trials as TopicMathematicsEvent (probability theory)Likelihood FunctionsModels StatisticalTerm (time)Sample size determinationSample SizeRegression AnalysisSubstance Abuse Treatment CentersStatistics in Medicine
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On delocalization of eigenvectors of random non-Hermitian matrices

2019

We study delocalization of null vectors and eigenvectors of random matrices with i.i.d entries. Let $A$ be an $n\times n$ random matrix with i.i.d real subgaussian entries of zero mean and unit variance. We show that with probability at least $1-e^{-\log^{2} n}$ $$ \min\limits_{I\subset[n],\,|I|= m}\|{\bf v}_I\| \geq \frac{m^{3/2}}{n^{3/2}\log^Cn}\|{\bf v}\| $$ for any real eigenvector ${\bf v}$ and any $m\in[\log^C n,n]$, where ${\bf v}_I$ denotes the restriction of ${\bf v}$ to $I$. Further, when the entries of $A$ are complex, with i.i.d real and imaginary parts, we show that with probability at least $1-e^{-\log^{2} n}$ all eigenvectors of $A$ are delocalized in the sense that $$ \min\l…

Statistics and ProbabilityZero mean010102 general mathematicsNull (mathematics)Probability (math.PR)01 natural sciencesHermitian matrixCombinatorics010104 statistics & probabilityDelocalized electronFOS: Mathematics0101 mathematicsStatistics Probability and UncertaintyRandom matrixUnit (ring theory)Mathematics - ProbabilityAnalysisEigenvalues and eigenvectorsMathematicsProbability Theory and Related Fields
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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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A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS

2019

We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Phase transitionrandom environmentGeneral Mathematicsmedia_common.quotation_subjectmoderate deviationslimit-theoremsmarkov-chainsStatistics::Other StatisticsBranching processdeviation inequalities92D2501 natural sciencesAsymmetry010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Convergence (routing)[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Applied mathematics60C05[MATH]Mathematics [math]0101 mathematicsautoregressive process60J20lawMathematicsBranching processmedia_commonEvent (probability theory)parametersconvergenceMarkov chain010102 general mathematics[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO][MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Large deviationslarge deviations Mathematics Subject Classification (2010): 60J8060K37Autoregressive modelcellsLarge deviations theoryStatistics Probability and Uncertaintyasymmetry60F10
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Resuming Shapes with Applications

2004

Many image processing tasks need some kind of average of different shapes. Frequently, different shapes obtained from several images have to be summarized. If these shapes can be considered as different realizations of a given random compact set, then the natural summaries are the different mean sets proposed in the literature. In this paper, new mean sets are defined by using the basic transformations of Mathematical Morphology (dilation, erosion, opening and closing). These new definitions can be considered, under some additional assumptions, as particular cases of the distance average of Baddeley and Molchanov. The use of the former and new mean sets as summary descriptors of shapes is i…

Statistics and Probabilitybusiness.industryApplied MathematicsNoise reductionImage processingMathematical morphologyCondensed Matter PhysicsConfidence intervalCompact spaceModeling and SimulationRandom compact setDilation (morphology)SegmentationComputer visionGeometry and TopologyComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmMathematicsJournal of Mathematical Imaging and Vision
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Estimation of total electricity consumption curves by sampling in a finite population when some trajectories are partially unobserved

2019

International audience; Millions of smart meters that are able to collect individual load curves, that is, electricity consumption time series, of residential and business customers at fine scale time grids are now deployed by electricity companies all around the world. It may be complex and costly to transmit and exploit such a large quantity of information, therefore it can be relevant to use survey sampling techniques to estimate mean load curves of specific groups of customers. Data collection, like every mass process, may undergo technical problems at every point of the metering and collection chain resulting in missing values. We consider imputation approaches (linear interpolation, k…

Statistics and Probabilityconstructionkernel smoothingPopulationSurvey samplingimputation01 natural sciences010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0502 economics and businessStatisticsImputation (statistics)0101 mathematicseducationsurvey samplingfunctional data050205 econometrics Mathematicsconfidence bandsConsumption (economics)Estimationeducation.field_of_studymissing completely at randombusiness.industry05 social sciencesprincipal analysis by conditional estimationSampling (statistics)[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]nearest neighboursKernel smoothervariance-estimationElectricityStatistics Probability and Uncertaintybusinessvariance approximation
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