Search results for "Copula"

showing 10 items of 59 documents

Mating strategies and resulting patterns in mate guarding crustaceans : an empirical and theoretical approach

2012

Because of strong costs associated with each mating event, females are usually not as available for reproduction as males at any given time. Males are therefore in competition with each other for access to receptive females, hence leading to strong sexual selection. One textbook case of such a mating system occurs in moulting crustaceans where females can only be fertilized during a short period following their moult. This has favoured the evolution male strategies to monopolize females before their period of receptivity. Such a precopulatory mate guarding is widespread among many taxa and represents one of the most striking example of males’ competitive traits favoured by sexual selection.…

Precopulatory mate guardingSexual conflictMate choiceGardiennage précopulatoireChoix de partenaireAmphipodAmphipodesConflit sexuelPatron de reproductionAssortative matingSexual selectionMating patternSélection sexuelleHomogamie pour la taille[SDV.BDLR] Life Sciences [q-bio]/Reproductive Biology
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Effect of host plant quality on male sexual performances and consequences on female reproductive output in a phytophagous moth

2016

The abundance of phytophagous insects is determined by numerous interacting biotic and abiotic factors. In capital-breeding phytophagous insects, larval host plant quality is a key determinant of the adult phenotype and the performance of both males and females. Curiously, if the effect of host plant quality on female reproductive success is well-established, little effort has been conducted to determine this effect on male reproductive success. Moreover, in Lepidoptera, males transfer to females a spermatophore containing sperm and accessory gland products rich in nutrients that could be reinvested into female reproduction. The aim of this thesis was to evaluate how male larval nutrition o…

Qualité du mâleSuccès reproducteurNutrition larvaire[SDV.BA] Life Sciences [q-bio]/Animal biologyMating successSpermatophoreDirect benefitsMale quality[SDV.EE] Life Sciences [q-bio]/Ecology environmentLobesia botranaInteractions plantes-insectesLarval nutritionComportements précopulatoiresInsect-plant interactionsBénéfices directs[SDV.BDLR] Life Sciences [q-bio]/Reproductive BiologyPrecopulatory behaviors
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Multivariate statistical analysis for water demand modelling: implementation, performance analysis, and comparison with the PRP model

2015

Water demand is the driving force behind hydraulic dynamics in water distribution systems. Consequently, it is crucial to accurately estimate the actual water use to develop reliable simulation models. In this study, copula-based multivariate analysis was proposed and used for demand prediction for a given return period. The analysis was applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach produced consistent demand patterns and could be a powerful tool when coupled with water distribution network models for design or analysis problems. The results were compared with those obtained using a classical water demand model, the Poisson re…

Return periodAtmospheric ScienceEngineeringMultivariate statisticsMultivariate analysisDemand patterns0208 environmental biotechnology02 engineering and technologyPoisson distributionCopula (probability theory)Vine copulasymbols.namesakeStatisticsEconometricsmultivariate analysiwater demand modellingCivil and Structural EngineeringWater Science and Technologybusiness.industryGeotechnical Engineering and Engineering Geology020801 environmental engineeringvine copulasymbolsPoisson rectangular pulse modelbusinessWater useJournal of Hydroinformatics
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Multivariate Statistical Analysis for Water Demand Modeling

2014

The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems. (C) 2014 Published by Elsevier Ltd.

Return periodMultivariate analysisMultivariate analysiDemand patternsSimulation modelingGeneral Medicinewater demand modeling.Copula (probability theory)Water demandVine copulaMultivariate analysisvine copulaStatisticsEconometricsEnvironmental scienceMultivariate statisticalEngineering(all)water demand modelingProcedia Engineering
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Uncertainty connected with design rainfall for urban flood risk evaluation

2010

Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaCopula functions multivariate analysis synthetic rainfall rainfall pattern urban flood risk
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On VaR using modified gaussian copula

2008

The problem of modeling asset returns is one of the most important issue in finance. People generally use Gaussian processes because of their tractable properties for computation. However, it is well known that asset returns are fat-tailed leading to an underestimation of the risk. One of the most recent proposals is to model the interdependence of asset returns, for example in a portfolio, by means of Copulas and choose marginal distributions with fat tail to fit the single asset returns. The aim of the paper is to show first results concerning the evaluation of Portfolio Value-at-Risk (VaR) using the Gaussian copula, modified by introducing a particular correlation coefficient, and assumi…

Settore SECS-S/01 - StatisticaValue at risk copulanon gaussian distributions
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Extending graphical models for applications: on covariates, missingness and normality

2021

The authors of the paper “Bayesian Graphical Models for Modern Biological Applications” have put forward an important framework for making graphical models more useful in applied settings. In this discussion paper, we give a number of suggestions for making this framework even more suitable for practical scenarios. Firstly, we show that an alternative and simplified definition of covariate might make the framework more manageable in high-dimensional settings. Secondly, we point out that the inclusion of missing variables is important for practical data analysis. Finally, we comment on the effect that the Gaussianity assumption has in identifying the underlying conditional independence graph…

Statistics and ProbabilityComputer sciencemedia_common.quotation_subjectMissing dataConditional graphical modelsCopula graphical modelsMissing dataCovariateEconometricsSparse inferenceGraphical modelStatistics Probability and UncertaintyNormalitymedia_common
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Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach

2019

Abstract This paper develops a novel approach to assess liquidity-adjusted Value-at-Risk (LVaR) optimization of multi-asset portfolios based on vine copulas and LVaR models. This framework is applied to stock markets of the G-7 countries, gold, commodities and Bitcoin. The results show that our approach is superior to the classical mean–variance Markowitz portfolio technique in terms of the optimal portfolio selection under a number of realistic operational and budget constraints. We find that both Bitcoin and gold improves the risk-return performance of the G-7 stock portfolio. However, Bitcoin (gold) performs better under a scenario of only long-positions (when short-selling is allowed).

Statistics and ProbabilityCondensed Matter Physics01 natural sciences010305 fluids & plasmasMarket liquidityVine copulaStock portfolio0103 physical sciencesEconometricsEconomicsPortfolioPortfolio optimization010306 general physicsBudget constraintValue at riskStock (geology)Physica A: Statistical Mechanics and its Applications
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Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials

2017

Abstract Many applications in risk analysis require the estimation of the dependence among multivariate maxima, especially in environmental sciences. Such dependence can be described by the Pickands dependence function of the underlying extreme-value copula. Here, a nonparametric estimator is constructed as the sample equivalent of a multivariate extension of the madogram. Shape constraints on the family of Pickands dependence functions are taken into account by means of a representation in terms of Bernstein polynomials. The large-sample theory of the estimator is developed and its finite-sample performance is evaluated with a simulation study. The approach is illustrated with a dataset of…

Statistics and ProbabilityFOS: Computer and information sciencesMultivariate statisticsNONPARAMETRIC ESTIMATIONMULTIVARIATE MAX-STABLE DISTRIBUTION01 natural sciencesCopula (probability theory)Methodology (stat.ME)010104 statistics & probabilityStatisticsStatistics::Methodology0101 mathematicsExtreme-value copulaEXTREMAL DEPENDENCEEXTREMEVALUE COPULA[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentStatistics - MethodologyComputingMilieux_MISCELLANEOUSMathematics[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereApplied Mathematics010102 general mathematicsNonparametric statisticsEstimatorExtremal dependenceHEAVY RAINFALLBernstein polynomialBERNSTEIN POLYNOMIALS EXTREMAL DEPENDENCE EXTREMEVALUE COPULA HEAVY RAINFALL NONPARAMETRIC ESTIMATION MULTIVARIATE MAX-STABLE DISTRIBUTION PICKANDS DEPENDENCE FUNCTION13. Climate actionDependence functionStatistics Probability and UncertaintyMaximaSettore SECS-S/01 - StatisticaBERNSTEIN POLYNOMIALSPICKANDS DEPENDENCE FUNCTION
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Dynamic copula models for the spark spread

2011

We propose a non-symmetric copula to model the evolution of electricity and gas prices by a bivariate non-Gaussian autoregressive process. We identify the marginal dynamics as driven by normal inverse Gaussian processes, estimating them from a series of observed UK electricity and gas spot data. We estimate the copula by modeling the difference between the empirical copula and the independent copula. We then simulate the joint process and price options written on the spark spread. We find that option prices are significantly influenced by the copula and the marginal distributions, along with the seasonality of the underlying prices.

Statistics::TheoryMathematical financeCopula (linguistics)Statistics::Other StatisticsBivariate analysisLévy processStatistics::ComputationInverse Gaussian distributionsymbols.namesakeAutoregressive modelSpark spreadStatisticsEconometricssymbolsEconomicsStatistics::MethodologyMarginal distributionGeneral Economics Econometrics and FinanceFinanceQuantitative Finance
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