Fabrizio Durante


Ontology type: schema:Person     


Person Info

NAME

Fabrizio

SURNAME

Durante

Publications in SciGraph latest 50 shown

  • 2018-12-01 Spatially homogeneous copulas in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 2018-02-22 A Graphical Tool for Copula Selection Based on Tail Dependence in CLASSIFICATION, (BIG) DATA ANALYSIS AND STATISTICAL LEARNING
  • 2017-10-14 Copula–based clustering methods in COPULAS AND DEPENDENCE MODELS WITH APPLICATIONS
  • 2017-05-19 Conditional risk based on multivariate hazard scenarios in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2017-01 Distribuzioni con marginali assegnate: Gli Inizi Un’intervista Con Giorgio Dall’Aglio in LETTERA MATEMATICA PRISTEM
  • 2016-11-23 Quantification of the environmental structural risk with spoiling ties: is randomization worthwhile? in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2016-07-30 A Test for Truncation Invariant Dependence in SOFT METHODS FOR DATA SCIENCE
  • 2016-07-30 A Multivariate Analysis of Tourists’ Spending Behaviour in SOFT METHODS FOR DATA SCIENCE
  • 2016-01-12 Asymmetric Copulas and Their Application in Design of Experiments in ON LOGICAL, ALGEBRAIC, AND PROBABILISTIC ASPECTS OF FUZZY SET THEORY
  • 2015-06-28 Spin-off Extreme Value and Archimedean copulas for estimating the bivariate structural risk in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2015-06-02 Copulas Based on Marshall–Olkin Machinery in MARSHALL ̶ OLKIN DISTRIBUTIONS - ADVANCES IN THEORY AND APPLICATIONS
  • 2015 Connectedness Measures of Spatial Contagion in the Banking and Insurance Sector in STRENGTHENING LINKS BETWEEN DATA ANALYSIS AND SOFT COMPUTING
  • 2015 Cluster Analysis of Time Series via Kendall Distribution in STRENGTHENING LINKS BETWEEN DATA ANALYSIS AND SOFT COMPUTING
  • 2014-11-18 Simulating from a Family of Generalized Archimedean Copulas in TOPICS IN STATISTICAL SIMULATION
  • 2014-06-13 Clustering of time series via non-parametric tail dependence estimation in STATISTICAL PAPERS
  • 2014-03-18 Estimation procedures for exchangeable Marshall copulas with hydrological application in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2014 Pairwise and Global Dependence in Trivariate Copula Models in INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS
  • 2013-12-22 Clustering of financial time series in risky scenarios in ADVANCES IN DATA ANALYSIS AND CLASSIFICATION
  • 2013 How to Prove Sklar’s Theorem in AGGREGATION FUNCTIONS IN THEORY AND IN PRACTISE
  • 2013 A Spatial Contagion Test for Financial Markets in SYNERGIES OF SOFT COMPUTING AND STATISTICS FOR INTELLIGENT DATA ANALYSIS
  • 2013 Copulas, Tail Dependence and Applications to the Analysis of Financial Time Series in AGGREGATION FUNCTIONS IN THEORY AND IN PRACTISE
  • 2013 Evolution of the Dependence of Residual Lifetimes in SYNERGIES OF SOFT COMPUTING AND STATISTICS FOR INTELLIGENT DATA ANALYSIS
  • 2011-09-14 Supermigrative copulas and positive dependence in ASTA ADVANCES IN STATISTICAL ANALYSIS
  • 2010-05-25 Copula Theory: An Introduction in COPULA THEORY AND ITS APPLICATIONS
  • 2010 Representation of Exchangeable Sequences by Means of Copulas in COMBINING SOFT COMPUTING AND STATISTICAL METHODS IN DATA ANALYSIS
  • 2009-05-16 Multivariate Hierarchical Copulas with Shocks in METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY
  • 2008-11-27 Bounds for Trivariate Copulas with Given Bivariate Marginals in JOURNAL OF INEQUALITIES AND APPLICATIONS
  • 2008-11-07 Non-exchangeability of negatively dependent random variables in METRIKA
  • 2008-07-01 Measures of non-exchangeability for bivariate random vectors in STATISTICAL PAPERS
  • 2008-01-01 On Patchwork Techniques for 2-Increasing Aggregation Functions and Copulas in SOFT METHODS FOR HANDLING VARIABILITY AND IMPRECISION
  • 2007-10 Conjunctors and their Residual Implicators: Characterizations and Construction Methods in MEDITERRANEAN JOURNAL OF MATHEMATICS
  • 2007-05-12 Construction of non-exchangeable bivariate distribution functions in STATISTICAL PAPERS
  • 2006-08-01 A Generalization of the Archimedean Class of Bivariate Copulas in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 2005-06-28 On a family of copulas constructed from the diagonal section in SOFT COMPUTING
  • 2004 Compositions of Copulas and Quasi-Copulas in SOFT METHODOLOGY AND RANDOM INFORMATION SYSTEMS
  • JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "affiliation": [
          {
            "affiliation": {
              "id": "http://www.grid.ac/institutes/grid.9906.6", 
              "type": "Organization"
            }, 
            "isCurrent": true, 
            "type": "OrganizationRole"
          }, 
          {
            "id": "http://www.grid.ac/institutes/grid.9970.7", 
            "type": "Organization"
          }, 
          {
            "id": "http://www.grid.ac/institutes/grid.34988.3e", 
            "type": "Organization"
          }
        ], 
        "familyName": "Durante", 
        "givenName": "Fabrizio", 
        "id": "sg:person.013475607471.22", 
        "identifier": [
          {
            "name": "orcid_id", 
            "type": "PropertyValue", 
            "value": "0000-0002-4899-1080"
          }
        ], 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013475607471.22", 
          "https://orcid.org/0000-0002-4899-1080"
        ], 
        "sdDataset": "persons", 
        "sdDatePublished": "2022-01-01T19:57", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/person/person_758.jsonl", 
        "type": "Person"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/person.013475607471.22'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/person.013475607471.22'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/person.013475607471.22'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/person.013475607471.22'


     
     




    Preview window. Press ESC to close (or click here)


    ...