Search results for " Uncertainty"

showing 10 items of 777 documents

Multivariate Nonparametric Tests

2004

Multivariate nonparametric statistical tests of hypotheses are described for the one-sample location problem, the several-sample location problem and the problem of testing independence between pairs of vectors. These methods are based on affine-invariant spatial sign and spatial rank vectors. They provide affine-invariant multivariate generalizations of the univariate sign test, signed-rank test, Wilcoxon rank sum test, Kruskal–Wallis test, and the Kendall and Spearman correlation tests. While the emphasis is on tests of hypotheses, certain references to associated affine-equivariant estimators are included. Pitman asymptotic efficiencies demonstrate the excellent performance of these meth…

Statistics and Probabilityeducation.field_of_studyMultivariate statisticsspatial signWilcoxon signed-rank testGeneral MathematicsRank (computer programming)PopulationNonparametric statisticsUnivariaterobustnessSpearman's rank correlation coefficientspatial rankPitman efficiencyStatisticsAffine invarianceEconometricsSign testStatistics::MethodologyStatistics Probability and UncertaintyeducationMathematics
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Spatial Mark-Recapture Method in the Estimation of Crayfish Population Size

1995

The mark-recapture method is considered for estimation of population size of slowly moving animals like crayfish. The Petersen type estimator for closed population is generalized for situations where recaptures are spatially dependent between the capture sites, and its variance approximation is derived using point processes as models for the population. The method of quadratic forms is suggested to be used as variance estimator. Finally, a trapping design is proposed where onc trap at recapture is replaced by four adjacent traps. A simulation experiment is performed to explain the robusticity of the new trapping design against movements of animals.

Statistics and Probabilityeducation.field_of_studyPopulation sizePopulationEstimatorGeneral MedicineTrappingCrayfishPoint processMark and recaptureStatisticsStatistics Probability and UncertaintySpatial dependenceeducationMathematicsBiometrical Journal
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Efficient Estimation of Non-Linear Finite Population Parameters by Using Non-Parametrics

2013

Summary Currently, high precision estimation of non-linear parameters such as Gini indices, low income proportions or other measures of inequality is particularly crucial. We propose a general class of estimators for such parameters that take into account univariate auxiliary information assumed to be known for every unit in the population. Through a non-parametric model-assisted approach, we construct a unique system of survey weights that can be used to estimate any non-linear parameter that is associated with any study variable of the survey, using a plug-in principle. Based on a rigorous functional approach and a linearization principle, the asymptotic variance of the estimators propose…

Statistics and Probabilityeducation.field_of_studyPopulationUnivariateEstimatorVariance (accounting)Delta methodLinearizationStatisticsEconometricsStatistics Probability and UncertaintyeducationSmoothingParametric statisticsMathematicsJournal of the Royal Statistical Society Series B: Statistical Methodology
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A Random Field Approach to Transect Counts of Wildlife Populations

1991

Line transect counting of a wildlife population is considered a sampling from a planar marked point process, where the marks describe the detectability of the animals. Sampling properties of transect counts and a new density estimator are derived from a counting process, which is a shot-noise field induced by the marked point process. A general formula for the sampling variance of a transect is derived and applied to compare five common types of transects. Some stereological connections of transect sampling and density estimators are shown.

Statistics and Probabilityeducation.field_of_studyRandom fieldCounting processCovariance functionPopulationSampling (statistics)EstimatorGeneral MedicineDensity estimationStatisticsStatistics Probability and UncertaintyeducationTransectMathematicsBiometrical Journal
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Role of sub- and super-Poisson noise sources in population dynamics

2020

In this paper we present a study on pulse noise sources characterized by sub- and super-Poisson statistics. We make a comparison with their uncorrelated counterpart. i.e. pulse noise with Poisson statistics, while showing that the correlation properties of sub- and super-Poisson noise sources can be efficiently applied to population dynamics. Specifically, we consider a termite population, described by a Langevin equation in the presence of a pulse noise source, and we study its dynamics and stability properties for two models. The first one describes a population of several colonies in a new territory with adverse environmental conditions. The second one considers the development of a sing…

Statistics and Probabilityeducation.field_of_studyStochastic processCorrelation functions Fluctuation phenomena Population dynamics Stochastic processesDynamics (mechanics)PopulationShot noiseStatistical and Nonlinear PhysicsStatistical physicsStatistics Probability and UncertaintyeducationMathematicsJournal of Statistical Mechanics: Theory and Experiment
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On implementation of the Gibbs sampler for estimating the accuracy of multiple diagnostic tests

2010

Implementation of the Gibbs sampler for estimating the accuracy of multiple binary diagnostic tests in one population has been investigated. This method, proposed by Joseph, Gyorkos and Coupal, makes use of a Bayesian approach and is used in the absence of a gold standard to estimate the prevalence, the sensitivity and specificity of medical diagnostic tests. The expressions that allow this method to be implemented for an arbitrary number of tests are given. By using the convergence diagnostics procedure of Raftery and Lewis, the relation between the number of iterations of Gibbs sampling and the precision of the estimated quantiles of the posterior distributions is derived. An example conc…

Statistics and Probabilityeducation.field_of_studygastroesophageal reflux diseaseBayesian probabilityPopulationGold standard (test)Settore FIS/03 - Fisica Della MateriaGibbs sampler; Bayesian analysis; convergence diagnostics; diagnostic tests; gastroesophageal reflux diseaseSettore MED/01 - Statistica MedicaData setsymbols.namesakediagnostic testGibbs samplerConvergence (routing)Statisticsconvergence diagnosticsymbolsSensitivity (control systems)Statistics Probability and UncertaintyeducationAlgorithmBayesian analysiQuantileMathematicsGibbs samplingJournal of Applied Statistics
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Extremal polynomials in stratified groups

2018

We introduce a family of extremal polynomials associated with the prolongation of a stratified nilpotent Lie algebra. These polynomials are related to a new algebraic characterization of abnormal subriemannian geodesics in stratified nilpotent Lie groups. They satisfy a set of remarkable structure relations that are used to integrate the adjoint equations.

Statistics and Probabilityextremal polynomialsMathematics - Differential GeometryPure mathematicsGeodesicStructure (category theory)Group Theory (math.GR)Characterization (mathematics)algebra01 natural sciencesdifferentiaaligeometriaMathematics - Analysis of PDEsMathematics - Metric Geometry53C17FOS: Mathematics0101 mathematicsAlgebraic numberMathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17; 49K30; 17B70Mathematics - Optimization and ControlMathematics010102 general mathematicsStatisticsta111polynomitProlongation53C17 49K30 17B70Lie groupMetric Geometry (math.MG)abnormal extremals010101 applied mathematicsNilpotent Lie algebraNilpotentsub-Riemannian geometryabnormal extremals extremal polynomials Carnot groups sub-Riemannian geometryAbnormal extremals; Carnot groups; Extremal polynomials; Sub-Riemannian geometry; Analysis; Statistics and Probability; Geometry and Topology; Statistics Probability and UncertaintyDifferential Geometry (math.DG)Optimization and Control (math.OC)Carnot groups17B70Probability and UncertaintyGeometry and TopologyStatistics Probability and UncertaintyMathematics - Group TheoryAnalysisAnalysis of PDEs (math.AP)Mathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17 49K30 17B7049K30
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Bioclimatic atlas of the terrestrial Arctic

2023

AbstractThe Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950–2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets…

Statistics and Probabilityhiilidioksidiarctic regionmeltingclimate changeswarmingPhysiologyEventsrainfallLibrary and Information SciencesklimatologiaEducationeliömaantiedeSnowilmastoSpecies distribution modelsVariabilityClimate-changeclimate1172 Environmental sciencesbiogeographyarktinen aluetemperaturecarbon dioxidesulaminenclimatologyilmastonmuutoksetecosystems (ecology)ekologiaComputer Science Applicationsekosysteemit (ekologia)sademääräclimate changeImpactsSea-icelämpötilaStatistics Probability and UncertaintyTrendslämpeneminenInformation Systemsclimate-change ecology
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Fourth Moments and Independent Component Analysis

2015

In independent component analysis it is assumed that the components of the observed random vector are linear combinations of latent independent random variables, and the aim is then to find an estimate for a transformation matrix back to these independent components. In the engineering literature, there are several traditional estimation procedures based on the use of fourth moments, such as FOBI (fourth order blind identification), JADE (joint approximate diagonalization of eigenmatrices), and FastICA, but the statistical properties of these estimates are not well known. In this paper various independent component functionals based on the fourth moments are discussed in detail, starting wi…

Statistics and ProbabilityjadeMultivariate random variableGeneral MathematicsMathematics - Statistics TheoryStatistics Theory (math.ST)02 engineering and technologyEstimating equations01 natural sciences010104 statistics & probabilityTransformation matrixFastICAFOS: Mathematics0202 electrical engineering electronic engineering information engineeringAffine equivarianceApplied mathematics0101 mathematicsLinear combinationMathematicsComponent (thermodynamics)kurtosis020206 networking & telecommunicationsFOBIIndependent component analysisJADEFastICAStatistics Probability and UncertaintyRandom variable
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Bayesian Modeling of Sequential Discoveries

2022

We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via accumulation curves, which count the number of distinct entities observed in an increasingly large set of objects. We propose a novel Bayesian method for species sampling modelling by directly specifying the probability of a new discovery, therefore allowing for flexible specifications. The asymptotic behavior and finite sample properties of such an approach are extensively studied. Interestingly, our enlarged class of sequential processes includes highly tr…

Statistics and Probabilitylajistokartoitusspecies sampling modelslogistic regressionbayesilainen menetelmäaccumulation curvesotantaStatistics Probability and Uncertaintydirichlet processtilastolliset mallitpoisson-binomial distribution
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