Search results for "conditional probability"

showing 10 items of 63 documents

Spatial dynamics of an invasive bird species assessed using robust design occupancy analysis: the case of the Eurasian collared dove ( Streptopelia d…

2007

Aim  The study of the spatial dynamics of invasive species is a key issue in invasion ecology. While mathematical models are useful for predicting the extent of population expansions, they are not suitable for measuring and characterizing spatial patterns of invasion unless the probability of detection is homogeneous across the distribution range. Here, we apply recently developed statistical approaches incorporating detection uncertainty to characterize the spatial dynamics of an invasive bird species, the Eurasian collared dove (Streptopelia decaocto). Location  France. Methods  Data on presence/absence of doves were recorded from 1996 to 2004 over 1045 grid cells (28 × 20 km) covering th…

0106 biological sciencesOccupancyRange (biology)PopulationMetapopulationSpatial distribution010603 evolutionary biology01 natural sciences[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsStatisticseducationComputingMilieux_MISCELLANEOUSEcology Evolution Behavior and Systematics[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologyeducation.field_of_studyEcologybiologyEcology010604 marine biology & hydrobiologyStreptopeliaConditional probability15. Life on landbiology.organism_classification[ SDV.EE.ECO ] Life Sciences [q-bio]/Ecology environment/EcosystemsGeographySpatial ecology[SDE.BE]Environmental Sciences/Biodiversity and EcologyJournal of Biogeography
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Predictive distributions that mimic frequencies over a restricted subdomain

2020

A predictive distribution over a sequence of $$N+1$$ events is said to be “frequency mimicking” whenever the probability for the final event conditioned on the outcome of the first N events equals the relative frequency of successes among them. Exchangeable distributions that exhibit this feature universally are known to have several annoying concomitant properties. We motivate frequency mimicking assertions over a limited subdomain in practical problems of finite inference, and we identify their computable coherent implications. We provide some examples using reference distributions, and we introduce computational software to generate any complete specification desired. Theorems on reducti…

A_n and H_n distributionSequenceSettore MAT/06 - Probabilita' E Statistica MatematicaComputer scienceConditional probabilityInferenceFrequencyOutcome (probability)Reduction (complexity)Distribution (mathematics)Settore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Probability elicitationExtendable exchangeabilityFeature (machine learning)Probability boundSettore SECS-S/01 - StatisticaGeneral Economics Econometrics and FinanceAlgorithmFinanceEvent (probability theory)Decisions in Economics and Finance
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Probabilities of conditionals and previsions of iterated conditionals

2019

Abstract We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability to be the conditional probability. In our approach, however, we avoid triviality because the import-export principle is invalid. We then analyze an example of reasoning under partial knowledge where, given a conditional if A then C as information, the probability of A should intuitively increase. We explain this intuition by making some implicit background information explicit. We consider several (generalized) iterated conditionals, which allow…

Background informationSettore MAT/06 - Probabilita' E Statistica MatematicaInference02 engineering and technologyConditional probabilities and previsionTheoretical Computer ScienceConditional random quantitieAffirmation of the ConsequentArtificial Intelligence020204 information systemsFOS: Mathematics0202 electrical engineering electronic engineering information engineeringConjoined and iterated conditionalMathematicsIndependence and uncorrelation.Applied MathematicsProbability (math.PR)Conditional probabilityMathematics - LogicTrivialityIterated function020201 artificial intelligence & image processingLogic (math.LO)Mathematical economicsCoherenceSoftwareMathematics - ProbabilityIntuition
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Path integral solution for non-linear system enforced by Poisson White Noise

2008

Abstract In this paper the response in terms of probability density function of non-linear systems under Poisson White Noise is considered. The problem is handled via path integral (PI) solution that may be considered as a step-by-step solution technique in terms of probability density function. First the extension of the PI to the case of Poisson White Noise is derived, then it is shown that at the limit when the time step becomes an infinitesimal quantity the Kolmogorov–Feller (K–F) equation is fully restored enforcing the validity of the approximations made in obtaining the conditional probability appearing in the Chapman Kolmogorov equation (starting point of the PI). Spectral counterpa…

Characteristic function (probability theory)Mechanical EngineeringMathematical analysisFokker-Planck equationAerospace EngineeringConditional probabilityKolmogorov-Feller eqautionOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionWhite noiseCondensed Matter PhysicsPoisson distributionPath Integral Solutionsymbols.namesakeNuclear Energy and EngineeringPath integral formulationsymbolsFokker–Planck equationSettore ICAR/08 - Scienza Delle CostruzioniChapman–Kolmogorov equationCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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Vectors of Pairwise Item Preferences

2019

Neural embedding has been widely applied as an effective category of vectorization methods in real-world recommender systems. However, its exploration of users’ explicit feedback on items, to create good quality user and item vectors is still limited. Existing neural embedding methods only consider the items that are accessed by the users, but neglect the scenario when a user gives high or low rating to a particular item. In this paper, we propose Pref2Vec, a method to generate vector representations of pairwise item preferences, users and items, which can be directly utilized for machine learning tasks. Specifically, Pref2Vec considers users’ pairwise item preferences as elementary units. …

Computer scienceneuraalilaskentaInitialization02 engineering and technology010501 environmental sciencesRecommender systemMachine learningcomputer.software_genre01 natural sciences0202 electrical engineering electronic engineering information engineeringvectorizationPreference (economics)Independence (probability theory)0105 earth and related environmental sciencesbusiness.industryComputer Science::Information RetrievalsuosittelujärjestelmätConditional probabilityneural embeddingVectorization (mathematics)Benchmark (computing)020201 artificial intelligence & image processingPairwise comparisonArtificial intelligencebusinesscomputer
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On conditional probabilities and their canonical extensions to Boolean algebras of compound conditionals

2023

In this paper we investigate canonical extensions of conditional probabilities to Boolean algebras of conditionals. Before entering into the probabilistic setting, we first prove that the lattice order relation of every Boolean algebra of conditionals can be characterized in terms of the well-known order relation given by Goodman and Nguyen. Then, as an interesting methodological tool, we show that canonical extensions behave well with respect to conditional subalgebras. As a consequence, we prove that a canonical extension and its original conditional probability agree on basic conditionals. Moreover, we verify that the probability of conjunctions and disjunctions of conditionals in a rece…

Conditional subalgebraCanonical extensionSettore MAT/06 - Probabilita' E Statistica MatematicaArtificial IntelligenceApplied MathematicsConditional probabilityNonmonotonic reasoningConjunction and disjunction of conditionalBoolean algebras of conditionalSoftwareTheoretical Computer ScienceInternational Journal of Approximate Reasoning
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Role of conditional probability in multiscale stationary markovian processes.

2010

The aim of the paper is to understand how the inclusion of more and more time-scales into a stochastic stationary Markovian process affects its conditional probability. To this end, we consider two Gaussian processes: (i) a short-range correlated process with an infinite set of time-scales bounded from below, and (ii) a power-law correlated process with an infinite and unbounded set of time-scales. For these processes we investigate the equal position conditional probability P(x,t|x,0) and the mean First Passage Time T(L). The function P(x,t|x,0) can be considered as a proxy of the persistence, i.e. the fact that when a process reaches a position x then it spends some time around that posit…

Continuous-time stochastic processPure mathematicsStationary processStationary distributionStatistical Mechanics (cond-mat.stat-mech)Stochastic processStochastic ProcesseFokker-Plank EquationFOS: Physical sciencesOrnstein–Uhlenbeck processConditional probability distributionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)CombinatoricsStable processPhysics - Data Analysis Statistics and ProbabilityMarkovian processeFirst-hitting-time modelCondensed Matter - Statistical MechanicsData Analysis Statistics and Probability (physics.data-an)MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
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Durum wheat yield uncertainty under different tillage management practices and climatic conditions

2019

Abstract In the field of conservative agriculture, no-till (NT) management has been receiving increasing interest, with 45 million ha of land under no-till management in 1999 to 155 million ha in 2014. Up until now, no-till has only been observed to perform better under rainfed conditions, especially in dry climates mainly because the reduced tillage system retains more soil moisture. However, the adoption of alternative agricultural practices (NT) can be improved only if uncertain and consequent assumption of risk is well known and accepted. For these reasons, the aim of this research is (i) to define durum wheat suitability under NT soil management in terms of yield success probability an…

Conventional tillageNo-tillDurum wheat yieldClimatic trendCrop yieldSoil ScienceConditional probability04 agricultural and veterinary sciencesSettore AGR/02 - Agronomia E Coltivazioni ErbaceeTillageSoil managementAgronomy040103 agronomy & agricultureSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali0401 agriculture forestry and fisheriesAridity indexCropping systemArable landAgronomy and Crop ScienceEarth-Surface ProcessesMathematicsSoil and Tillage Research
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Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P

2016

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…

Deductive reasoningSettore MAT/06 - Probabilita' E Statistica MatematicaConditional probability assessments conditional constraints probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment defaultreasoning from conditional knowledge bases System P conditional objects.conditional constraintsLogicDefault logicStatistics::Other StatisticsProbabilistic logic networkConditional probability assessmentsprobabilistic logic under coherenceNon-monotonic logicSystem PMathematicsg-coherent entailmentHardware_MEMORYSTRUCTURESmodel-theoretic probabilistic logicbusiness.industryProbabilistic logicSystem P; g-coherence; conditional objectsCoherence (statistics)default reasoning from conditional knowledge basesProbabilistic argumentationConditional probability assessments; conditional constraints; probabilistic logic under coherence; model-theoretic probabilistic logic; g-coherence; g-coherent entailment; default reasoning from conditional knowledge bases; System P; conditional objects.Philosophyg-coherenceProbabilistic CTLArtificial intelligencebusinessAlgorithmconditional objectsJournal of Applied Non−Classical Logics
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Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning

2001

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…

Deductive reasoningSettore MAT/06 - Probabilita' E Statistica MatematicaKnowledge representation and reasoningComputer scienceDefault logicDivergence-from-randomness modelLogic modelcomputer.software_genreLogical consequenceProbabilistic logic networkConditional probability assessments conditional constraints probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment default reasoning from conditional knowledge bases System P conditional objectsprobabilistic logic under coherenceNon-monotonic logicProbabilistic relevance modeldefault reasoningmodel-theoretic probabilistic logicbusiness.industryProbabilistic logicProbabilistic argumentationExpert systemg-coherencesystem pProbabilistic CTLArtificial intelligencebusinesscomputerdefault reasoning; g-coherence; model-theoretic probabilistic logic; probabilistic logic under coherence; system p
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