0000000000303257

AUTHOR

Juan Ferrándiz

showing 13 related works from this author

Sparse Sampling and Maximum Likelihood Estimation for Boolean Models

1991

A condition for practical independence of contact distribution functions in Boolean models is obtained. This result allows the authors to use maximum likelihcod methods, via sparse sampling, for estimating unknown parameters of an isotropic Boolean model. The second part of this paper is devoted to a simulation study of the proposed method. AMS classification: 60D05

Statistics and ProbabilityBiometricsBoolean modelIsotropySampling (statistics)General MedicineLikelihood-ratio testStatisticsMaximum satisfiability problemStatistics Probability and UncertaintyAlgorithmIndependence (probability theory)Standard Boolean modelMathematicsBiometrical Journal
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Spatial Interaction between Neighbouring Counties: Cancer Mortality Data in Valencia (Spain)

1995

The statistical analysis of geographical mortality data has usually been approached via regression models that include appropriate covariates. These models assume stochastic independence of mortality counts for neighbouring sites, a questionable assumption that spatial automodels (Besag, 1974, Journal of the Royal Statistical Society, Series B 36, 192-236) make unnecessary. This paper presents the use of the autopoisson distribution in order to detect spatial interaction between neighbouring sites. If this interaction results in being nonsignificant, the auto-Poisson distribution reduces to a usual Poisson regression model, a particular case of generalized linear models (McCullagh and Nelde…

MaleStatistics and ProbabilityGeneralized linear modelGLIMPoisson distributionGeneral Biochemistry Genetics and Molecular Biologysymbols.namesakeStomach NeoplasmsNeoplasmsStatisticsCovariateHumansPoisson DistributionPoisson regressionFertilizersDemographyCancer mortalityModels StatisticalNitratesGeneral Immunology and MicrobiologyApplied MathematicsSpatial interactionProstatic NeoplasmsRegression analysisGeneral MedicineGeographyUrinary Bladder NeoplasmsSpainColonic NeoplasmssymbolsRegression AnalysisGeneral Agricultural and Biological SciencesDemographyBiometrics
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Statistical inference and Monte Carlo algorithms

1996

This review article looks at a small part of the picture of the interrelationship between statistical theory and computational algorithms, especially the Gibbs sampler and the Accept-Reject algorithm. We pay particular attention to how the methodologies affect and complement each other.

Statistics and ProbabilityDecision theoryMonte Carlo methodMarkov chain Monte CarloStatistics::ComputationComplement (complexity)symbols.namesakeStatistical inferencesymbolsMonte Carlo method in statistical physicsStatistics Probability and UncertaintyStatistical theoryAlgorithmGibbs samplingMathematicsTest
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Potential approach in marginalizing Gibbs models

1999

Abstract Given an undirected graph G or hypergraph potential H model for a given set of variables V , we introduce two marginalization operators for obtaining the undirected graph G A or hypergraph H A associated with a given subset A ⊂ V such that the marginal distribution of A factorizes according to G A or H A , respectively. Finally, we illustrate the method by its application to some practical examples. With them we show that potential approach allow defining a finer factorization or performing a more precise conditional independence analysis than undirected graph models. Finally, we explain connections with related works.

Discrete mathematicsApplied MathematicsComparability graphStrength of a graphClique graphlaw.inventionTheoretical Computer ScienceCombinatoricslawGraph powerArtificial IntelligenceGibbs modelLine graphGraph (abstract data type)FactorizationNull graphMarginalizationRandom geometric graphHypergraph modelsSoftwareMathematicsInternational Journal of Approximate Reasoning
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Simulation in the Simple Linear Regression Model

2002

Summary This article presents an activity which simulates the linear regression model in order to verify the probabilistic behaviour of the resulting least-squares statistics in practice.

Statistics and ProbabilityPolynomial regressionGeneral linear modelProper linear modelMultivariate adaptive regression splinesComputer scienceStatisticsLinear modelApplied mathematicsPrincipal component regressionLog-linear modelSimple linear regressionEducationTeaching Statistics
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Procesos puntuales como herramienta para el análisis de posibles fuentes de contaminación

2002

El análisis de un patrón puntual engloba una serie de técnicas que permiten estudiar la distribución de un conjunto de eventos ocurridos sobre una región del plano. Este problema surge en epidemiología cuando se investiga una potencial fuente de contaminación ambiental alrededor de la cual se sospecha que surgen casos de una determinada enfermedad. En el presente trabajo, se explica brevemente en qué consiste el análisis de un patrón puntual y se ilustra con una aplicación a la determinación del origen medioambiental y al estudio de las zonas de mayor riesgo de incidencia en un brote de neumonía por Legionella ocurrido entre mediados de septiembre y principios de octubre en la ciudad de Alc…

Proceso puntualContaminación ambientallcsh:Public aspects of medicinePublic Health Environmental and Occupational HealthSpatial analysisAnálisis espacialLegionellalcsh:RA1-1270Point processEnvironmental pollutionGaceta Sanitaria
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Spatial analysis of the relationship between mortality from cardiovascular and cerebrovascular disease and drinking water hardness

2004

Journal Article; Research Support, Non-U.S. Gov't; Reproduced with permission from Environmental Health Perspectives. Previously published scientific papers have reported a negative correlation between drinking water hardness and cardiovascular mortality. Some ecologic and case-control studies suggest the protective effect of calcium and magnesium concentration in drinking water. In this article we present an analysis of this protective relationship in 538 municipalities of Comunidad Valenciana (Spain) from 1991-1998. We used the Spanish version of the Rapid Inquiry Facility (RIF) developed under the European Environment and Health Information System (EUROHEIS) research project. The strateg…

GerontologyMaleMini-Monograph: Information SystemsHealth Toxicology and MutagenesisWater supply:Named Groups::Persons::Age Groups::Adult::Middle Aged [Medical Subject Headings]Disease:Health Care::Environment and Public Health::Public Health::Sanitation::Sanitary Engineering::Water Supply [Medical Subject Headings]Magnesio:Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings]PreescolarMediana EdadReference ValuesExposición a Riesgos AmbientalesMedicineCluster AnalysisMagnesiumMasculinoChildEnfermedades Cardiovascularesgeographic information systems:Named Groups::Persons::Age Groups::Child::Child Preschool [Medical Subject Headings]:Analytical Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Weights and Measures::Reference Values [Medical Subject Headings]AdultoAguaEpidemiologic SurveillanceEnvironmental exposureMiddle AgedHumanos:Health Care::Environment and Public Health::Public Health::Environmental Pollution::Environmental Exposure [Medical Subject Headings]Abastecimiento de aguarelative risk:Information Science::Information Science::Information Storage and Retrieval::Databases as Topic::Databases Factual::Geographic Information Systems [Medical Subject Headings]Cardiovascular DiseasesNiñoChild Preschool:Diseases::Nervous System Diseases::Central Nervous System Diseases::Brain Diseases::Cerebrovascular Disorders [Medical Subject Headings]Female:Named Groups::Persons::Age Groups::Infant [Medical Subject Headings]Risk assessmentAdulthierarchical spatial modelsAdolescentAncianoSistemas de Información Geográfica:Check Tags::Male [Medical Subject Headings]:Analytical Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Cluster Analysis [Medical Subject Headings]:Named Groups::Persons::Age Groups::Infant::Infant Newborn [Medical Subject Headings]Risk AssessmentCalcioWater Supply:Chemicals and Drugs::Inorganic Chemicals::Metals::Metals Alkaline Earth::Calcium [Medical Subject Headings]Environmental health:Named Groups::Persons::Age Groups::Adult [Medical Subject Headings]:Chemicals and Drugs::Inorganic Chemicals::Metals::Metals Light::Magnesium [Medical Subject Headings]Humans:Chemicals and Drugs::Inorganic Chemicals::Hydroxides::Water [Medical Subject Headings]:Named Groups::Persons::Age Groups::Adult::Aged [Medical Subject Headings]:Diseases::Cardiovascular Diseases [Medical Subject Headings]Socioeconomic status:Named Groups::Persons::Age Groups::Child [Medical Subject Headings]Agedbusiness.industry:Analytical Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Risk::Risk Assessment [Medical Subject Headings]Public Health Environmental and Occupational HealthInfant NewbornInfantWaterLactanteEnvironmental ExposureValores de ReferenciaAnálisis por ConglomeradosEstudios Epidemiológicosenvironmental epidemiologyCerebrovascular DisordersEpidemiologic StudiesTrastornos Cerebrovasculares:Check Tags::Female [Medical Subject Headings]Relative riskspatial smoothingCalciumbusinessMedición de Riesgo:Analytical Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies [Medical Subject Headings]Environmental epidemiology
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The foundations of decision theory: An intuitive, operational approach with mathematical extensions

1985

A new axiomatic basis for the foundations of decision theory is introduced and its mathematical development outlined. The system combines direct intuitive operational appeal with considerable structural flexibility in the resulting mathematical framework.

Decision engineeringManagement scienceDecision theoryEvidential reasoning approachGeneral Social SciencesGeneral Decision SciencesDecision ruleComputer Science ApplicationsArts and Humanities (miscellaneous)Developmental and Educational PsychologyInfluence diagramCausal decision theoryGeneral Economics Econometrics and FinanceApplied PsychologyAxiomMathematicsDecision analysisTheory and Decision
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Geographical Distribution of Cardiovascular Mortality in Comunidad Valenciana (Spain)

2002

Comunidad Valenciana is one of the seventeen autonomous regions into which Spain is divided. It is located on the east coast of Spain, next to the Mediterranean sea, with an area of 23,255 km2 and with 4,009,329 inhabitants in 1996. From an administrative point of view there are three levels of aggregation: provinces (3 units), health areas (20 units) and municipalities (541 units).

Deviance information criterionEast coastMediterranean seaGeographybusiness.industryDistribution (economics)Ischaemic heart diseaseSocioeconomicsbusinessCardiovascular mortality
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Statistical relationship between hardness of drinking water and cerebrovascular mortality in Valencia: a comparison of spatiotemporal models

2003

The statistical detection of environmental risk factors in public health studies is usually difficult due to the weakness of their effects and their confounding with other covariates. Small area geographical data bring the opportunity of observing health response in a wide variety of exposure values. Temporal sequences of these geographical datasets are crucial to gaining statistical power in detecting factors. The spatiotemporal models required to perform the statistical analysis have to allow for spatial and temporal correlations, which are more easily modelled via hierarchical structures of hidden random factors. These models have produced important research activity during the last deca…

Statistics and ProbabilityOperations researchComputer scienceEcological ModelingBayesian probabilityBayes factorMarkov chain Monte CarloDeviance (statistics)Information CriteriaStatistical powerDeviance information criterionsymbols.namesakeCovariateStatisticssymbolsEnvironmetrics
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Temporal aggregation in chain graph models

2005

The dependence structure of an observed process induced by temporal aggregation of a time evolving hidden spatial phenomenon is addressed. Data are described by means of chain graph models and an algorithm to compute the chain graph resulting from the temporal aggregation of a directed acyclic graph is provided. This chain graph is the best graph which covers the independencies of the resulting process within the chain graph class. A sufficient condition that produces a memory loss of the observed process with respect to its hidden origin is analyzed. Some examples are used for illustrating algorithms and results.

Statistics and ProbabilityApplied MathematicsVoltage graphDirected graphStrength of a graphTopologyGraph (abstract data type)Statistics Probability and UncertaintyNull graphGraph propertyAlgorithmComplement graphMathematicsofComputing_DISCRETEMATHEMATICSMoral graphMathematicsJournal of Statistical Planning and Inference
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Boolean Models: Maximum Likelihood Estimation from Circular Clumps

1990

This paper deals with the problem of making inferences on the maximum radius and the intensity of the Poisson point process associated to a Boolean Model of circular primary grains with uniformly distributed random radii. The only sample information used is observed radii of circular clumps (DUPAC, 1980). The behaviour of maximum likelihood estimation has been evaluated by means of Monte Carlo methods.

Statistics and ProbabilityMathematical optimizationEstimation theoryBoolean modelMonte Carlo methodMathematical analysisGeneral MedicineRadiusMaximum likelihood sequence estimationPoisson point processBoolean expressionStatistics Probability and UncertaintyIntensity (heat transfer)MathematicsBiometrical Journal
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Marginalizing in Undirected Graph and Hypergraph Models

2013

Given an undirected graph G or hypergraph X model for a given set of variables V, we introduce two marginalization operators for obtaining the undirected graph GA or hypergraph HA associated with a given subset A c V such that the marginal distribution of A factorizes according to GA or HA, respectively. Finally, we illustrate the method by its application to some practical examples. With them we show that hypergraph models allow defining a finer factorization or performing a more precise conditional independence analysis than undirected graph models.

FOS: Computer and information sciencesArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceComputer Science::Discrete Mathematics
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