Search results for "Functions"

showing 10 items of 1066 documents

MLML2R: an R package for maximum likelihood estimation of DNA methylation and hydroxymethylation proportions.

2019

Abstract Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which provides maximum likelihood estimates (MLE) of 5-mC and 5-hmC proportions. While all other available R packages provide 5-mC and 5-hmC MLEs only for the oxBS+BS combination, MLML2R also provides MLE for TAB combinations. For combinations of any two of the methods, we derived the pool-adjacent-violators algorithm (PAVA) exact constrained MLE in analytical form. For the…

Statistics and ProbabilityDNA HydroxymethylationEpigenomicsIterative methodMaximum likelihood03 medical and health sciencessymbols.namesake0302 clinical medicineGeneticsHumansMolecular Biology030304 developmental biologyMathematics0303 health sciencesLikelihood FunctionsComputational BiologyHigh-Throughput Nucleotide SequencingProbability and statisticsDNA MethylationComputational MathematicsR packageLagrange multiplierDNA methylationsymbolsIterative approximationAlgorithm030217 neurology & neurosurgeryStatistical applications in genetics and molecular biology
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Modeling temperature effects on mortality: multiple segmented relationships with common break points.

2008

We present a model for estimation of temperature effects on mortality that is able to capture jointly the typical features of every temperature-death relationship, that is, nonlinearity and delayed effect of cold and heat over a few days. Using a segmented approximation along with a doubly penalized spline-based distributed lag parameterization, estimates and relevant standard errors of the cold- and heat-related risks and the heat tolerance are provided. The model is applied to data from Milano, Italy.

Statistics and ProbabilityDistributed lagHot TemperatureTime FactorsInjury controlPoison controltemperature effectRisk FactorsStatisticsHumansSegmented regressionMortalitysegmented regressionWeatherSimulationMathematicsLikelihood FunctionsModels StatisticalTemperatureGeneral MedicineHeat toleranceCold TemperatureSpline (mathematics)Nonlinear systemStandard errorItalyNonlinear DynamicsLinear ModelsRegression AnalysisStatistics Probability and Uncertaintybreak pointSettore SECS-S/01 - StatisticaAlgorithmsBiostatistics (Oxford, England)
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Tailoring sparse multivariable regression techniques for prognostic single-nucleotide polymorphism signatures.

2011

When seeking prognostic information for patients, modern technologies provide a huge amount of genomic measurements as a starting point. For single-nucleotide polymorphisms (SNPs), there may be more than one million covariates that need to be simultaneously considered with respect to a clinical endpoint. Although the underlying biological problem cannot be solved on the basis of clinical cohorts of only modest size, some important SNPs might still be identified. Sparse multivariable regression techniques have recently become available for automatically identifying prognostic molecular signatures that comprise relatively few covariates and provide reasonable prediction performance. For illus…

Statistics and ProbabilityEpidemiologyComputer scienceFeature selectionBiostatisticscomputer.software_genrePolymorphism Single NucleotideLasso (statistics)Gene FrequencyResamplingCovariateHumansLikelihood FunctionsModels StatisticalMultivariable calculusRegression analysisGenomicsPrognosisRegressionMinor allele frequencyLeukemia Myeloid AcuteMultivariate AnalysisRegression AnalysisData miningcomputerAlgorithmsStatistics in medicine
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Confidence bands for Horvitz-Thompson estimators using sampled noisy functional data

2013

When collections of functional data are too large to be exhaustively observed, survey sampling techniques provide an effective way to estimate global quantities such as the population mean function. Assuming functional data are collected from a finite population according to a probabilistic sampling scheme, with the measurements being discrete in time and noisy, we propose to first smooth the sampled trajectories with local polynomials and then estimate the mean function with a Horvitz-Thompson estimator. Under mild conditions on the population size, observation times, regularity of the trajectories, sampling scheme, and smoothing bandwidth, we prove a Central Limit theorem in the space of …

Statistics and ProbabilityFOS: Computer and information sciencesmaximal inequalitiesCovariance functionCLTPopulationSurvey samplingweighted cross-validationMathematics - Statistics TheoryStatistics Theory (math.ST)Methodology (stat.ME)symbols.namesakeFOS: Mathematicssurvey samplingeducationGaussian processfunctional dataStatistics - Methodologysuprema of Gaussian processesMathematicsCentral limit theoremeducation.field_of_studySampling (statistics)Estimatorspace of continuous functionssymbolslocal polynomial smoothingAlgorithmSmoothing
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Asymptotics of correlation functions of the Heisenberg-Ising chain in the easy-axis regime

2016

We analyze the long-time large-distance asymptotics of the longitudinal correlation functions of the Heisenberg-Ising chain in the easy-axis regime. We show that in this regime the leading asymptotics of the dynamical two-point functions is entirely determined by the two-spinon contribution to their form factor expansion. Its explicit form is obtained from a saddle-point analysis of the corresponding double integral. It describes the propagation of a wave front with velocity $v_{c_1}$ which is found to be the maximal possible group velocity. Like in wave propagation in dispersive media the wave front is preceded by a precursor running ahead with velocity $v_{c_2}$. As a special case we obta…

Statistics and ProbabilityHigh Energy Physics - Theory[PHYS.COND.GAS]Physics [physics]/Condensed Matter [cond-mat]/Quantum Gases [cond-mat.quant-gas]Correlation functionsWave propagationExact asymptotic resultsGeneral Physics and AstronomyFOS: Physical sciences01 natural sciences010305 fluids & plasmas[ PHYS.COND.GAS ] Physics [physics]/Condensed Matter [cond-mat]/Quantum Gases [cond-mat.quant-gas][ PHYS.HTHE ] Physics [physics]/High Energy Physics - Theory [hep-th]Condensed Matter - Strongly Correlated ElectronsQuantum spin chain0103 physical sciencesQuantum communication010306 general physicsDispersion (water waves)Mathematical PhysicsSaddlePhysicsStrongly Correlated Electrons (cond-mat.str-el)[PHYS.HTHE]Physics [physics]/High Energy Physics - Theory [hep-th]Heisenberg modelMultiple integralMathematical analysisForm factor (quantum field theory)Statistical and Nonlinear PhysicsFunction (mathematics)High Energy Physics - Theory (hep-th)Quantum Gases (cond-mat.quant-gas)Modeling and Simulation[ PHYS.COND.CM-SCE ] Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]Group velocity[PHYS.COND.CM-SCE]Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]Condensed Matter - Quantum Gases
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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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Multitype spatial point patterns with hierarchical interactions.

2001

Multitype spatial point patterns with hierarchical interactions are considered. Here hierarchical interaction means directionality: points on a higher level of hierarchy affect the locations of points on the lower levels, but not vice versa. Such relations are common, for example, in ecological communities. Interacting point patterns are often modeled by Gibbs processes with pairwise interactions. However, these models are inherently symmetric, and the hierarchy can be acknowledged only when interpreting the results. We suggest the following in allowing the inclusion of the hierarchical structure in the model. Instead of regarding the pattern as a realization of a stationary multivariate po…

Statistics and ProbabilityLikelihood FunctionsBiometryModels StatisticalGeneral Immunology and MicrobiologyHierarchy (mathematics)AntsApplied MathematicsStructure (category theory)UnivariateGeneral MedicineType (model theory)General Biochemistry Genetics and Molecular BiologyPoint processCombinatoricsSpecies SpecificityMultivariate AnalysisAnimalsPairwise comparisonPoint (geometry)Statistical physicsGeneral Agricultural and Biological SciencesRealization (probability)EcosystemMathematicsBiometrics
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Comprehensive estimation of input signals and dynamics in biochemical reaction networks

2012

Abstract Motivation: Cellular information processing can be described mathematically using differential equations. Often, external stimulation of cells by compounds such as drugs or hormones leading to activation has to be considered. Mathematically, the stimulus is represented by a time-dependent input function. Parameters such as rate constants of the molecular interactions are often unknown and need to be estimated from experimental data, e.g. by maximum likelihood estimation. For this purpose, the input function has to be defined for all times of the integration interval. This is usually achieved by approximating the input by interpolation or smoothing of the measured data. This procedu…

Statistics and ProbabilityMedicin och hälsovetenskapComputer scienceDifferential equationMaximum likelihoodcomputer.software_genreBiochemistryModels BiologicalMedical and Health SciencesIntegration intervalMolecular BiologyJanus KinasesLikelihood FunctionsRegulation Pathways and Systems BiologyExperimental dataOriginal PapersConfidence intervalComputer Science ApplicationsComputational MathematicsSTAT Transcription FactorsComputational Theory and MathematicsData miningAlgorithmcomputerSmoothingAlgorithmsSignal Transduction
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Fractional calculus approach to the statistical characterization of random variables and vectors

2009

Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has inverse power-law tails and, consequently, it lacks integer order moments. In this paper, starting from the Mellin transform of the characteristic function and by fractional calculus method we present a new perspective on the statistics of random variables. Introducing the class of complex moments, that include both integer and fractional moments, we show that every random variable can be represented within this approach, even if its integer moments diverge. A…

Statistics and ProbabilityMellin transformStatistical Mechanics (cond-mat.stat-mech)Characteristic function (probability theory)Multivariate distributionMultivariate random variableMathematical analysisFOS: Physical sciencesMoment-generating functionCondensed Matter PhysicsFractional calculusFractional and complex moments; Multivariate distributions; Power-law tails; Inverse Mellin transformFractional and complex momentIngenieurwissenschaftenApplied mathematicsddc:620Inverse Mellin transformSettore ICAR/08 - Scienza Delle CostruzioniRandom variableCondensed Matter - Statistical MechanicsMathematicsInteger (computer science)Taylor expansions for the moments of functions of random variablesPower-law tail
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Moments for Some Kumaraswamy Generalized Distributions

2014

Explicit expansions for the moments of some Kumaraswamy generalized (Kw-G) distributions (Cordeiro and de Castro, 2011) are derived using special functions. We explore the Kw-normal, Kw-gamma, Kw-beta, Kw-t, and Kw-F distributions. These expressions are given as infinite weighted linear combinations of well-known special functions for which numerical routines are readily available.

Statistics and ProbabilityNormal distributionSpecial functionsMathematical analysisGeneralized gamma distributionGeneralized beta distributionGeneralized integer gamma distributionLinear combinationInverse distributionVariance-gamma distributionMathematicsCommunications in Statistics - Theory and Methods
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