Correlation and dependence / Dominique Drouet Mari, Samuel Kotz |
Autore | Drouet Mari, Dominique |
Pubbl/distr/stampa | London : Imperial College Press |
Descrizione fisica | xiv, 219 p. : ill. ; 23 cm |
Disciplina | 519.537 |
Altri autori (Persone) | Kotz, Samuelauthor |
Soggetto topico |
Correlation (Statistics)
Dependence (Statistics) |
ISBN | 1860942644 |
Classificazione |
AMS 60E15
AMS 62H20 LC QA278.2.M36 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991001619879707536 |
Drouet Mari, Dominique | ||
London : Imperial College Press | ||
Materiale a stampa | ||
Lo trovi qui: Univ. del Salento | ||
|
Correlation and dependence [[electronic resource] /] / Dominique Drouet Mari, Samuel Kotz |
Autore | Mari Dominique Drouet |
Pubbl/distr/stampa | London, : Imperial College Press |
Descrizione fisica | 1 online resource (236 p.) |
Disciplina | 519.2 |
Altri autori (Persone) | KotzSamuel |
Soggetto topico |
Correlation (Statistics)
Dependence (Statistics) |
Soggetto genere / forma | Electronic books. |
ISBN |
1-281-86948-1
9786611869489 1-86094-975-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents ; Preface ; Chapter 1 Notations and Definitions ; 1.1 Notations ; 1.2 Definitions ; Chapter 2 Correlation and Dependence : An Introspection ; 2.1 Independence ; 2.2 Zero Correlation Versus Dependence ; 2.3 Some Geometrical Examples ; 2.4 Some Further Historical Remarks
2.5 A Brief Tour of Early Applications and Misinterpretations Chapter 3 Concepts of Dependence and Stochastic Ordering ; 3.1 Introduction ; 3.2 Concepts of Positive Dependence ; 3.3 Negative Dependence for More than Two Variables ; 3.4 Setwise Dependence ; 3.5 Other Approaches 3.6 Positive Dependence Orderings 3.7 Bayesian Approach to Stochastic Dependence ; Chapter 4 Copulas ; 4.1 Introduction ; 4.2 Definition and Some Properties ; 4.3 The Frechet Bounds ; 4.4 Examples ; 4.5 Construction of a Copula ; 4.6 Archimedean Copulas ; 4.7 Archimax Copulas 4.8 Copulas with Discontinuity Constraints 4.9 Copulas with More than Two Variables ; 4.10 Simulation Procedures ; Chapter 5 Farlie-Gumbel-Morgenstern Models of Dependence ; 5.1 Introduction ; 5.2 Initial Definition ; 5.3 Regression and Correlation ; 5.4 Iterations 5.5 Dependence Properties 5.6 A Class of n-variate FGM Distributions ; 5.7 Further Extensions ; 5.8 FGM Sequences ; Chapter 6 Global Versus Local Dependence between Random Variables ; 6.1 Introduction ; 6.2 Global Measures of Dependence ; 6.3 Local Indices of Dependence 6.4 Non-parametric Estimation of Local Indices |
Record Nr. | UNINA-9910454335103321 |
Mari Dominique Drouet | ||
London, : Imperial College Press | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Correlation and dependence [[electronic resource] /] / Dominique Drouet Mari, Samuel Kotz |
Autore | Mari Dominique Drouet |
Pubbl/distr/stampa | London, : Imperial College Press |
Descrizione fisica | 1 online resource (236 p.) |
Disciplina | 519.2 |
Altri autori (Persone) | KotzSamuel |
Soggetto topico |
Correlation (Statistics)
Dependence (Statistics) |
ISBN |
1-281-86948-1
9786611869489 1-86094-975-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents ; Preface ; Chapter 1 Notations and Definitions ; 1.1 Notations ; 1.2 Definitions ; Chapter 2 Correlation and Dependence : An Introspection ; 2.1 Independence ; 2.2 Zero Correlation Versus Dependence ; 2.3 Some Geometrical Examples ; 2.4 Some Further Historical Remarks
2.5 A Brief Tour of Early Applications and Misinterpretations Chapter 3 Concepts of Dependence and Stochastic Ordering ; 3.1 Introduction ; 3.2 Concepts of Positive Dependence ; 3.3 Negative Dependence for More than Two Variables ; 3.4 Setwise Dependence ; 3.5 Other Approaches 3.6 Positive Dependence Orderings 3.7 Bayesian Approach to Stochastic Dependence ; Chapter 4 Copulas ; 4.1 Introduction ; 4.2 Definition and Some Properties ; 4.3 The Frechet Bounds ; 4.4 Examples ; 4.5 Construction of a Copula ; 4.6 Archimedean Copulas ; 4.7 Archimax Copulas 4.8 Copulas with Discontinuity Constraints 4.9 Copulas with More than Two Variables ; 4.10 Simulation Procedures ; Chapter 5 Farlie-Gumbel-Morgenstern Models of Dependence ; 5.1 Introduction ; 5.2 Initial Definition ; 5.3 Regression and Correlation ; 5.4 Iterations 5.5 Dependence Properties 5.6 A Class of n-variate FGM Distributions ; 5.7 Further Extensions ; 5.8 FGM Sequences ; Chapter 6 Global Versus Local Dependence between Random Variables ; 6.1 Introduction ; 6.2 Global Measures of Dependence ; 6.3 Local Indices of Dependence 6.4 Non-parametric Estimation of Local Indices |
Record Nr. | UNINA-9910782123203321 |
Mari Dominique Drouet | ||
London, : Imperial College Press | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Correlation and dependence / / Dominique Drouet Mari, Samuel Kotz |
Autore | Mari Dominique Drouet |
Edizione | [1st ed.] |
Pubbl/distr/stampa | London, : Imperial College Press |
Descrizione fisica | 1 online resource (236 p.) |
Disciplina | 519.2 |
Altri autori (Persone) | KotzSamuel |
Soggetto topico |
Correlation (Statistics)
Dependence (Statistics) |
ISBN |
1-281-86948-1
9786611869489 1-86094-975-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents ; Preface ; Chapter 1 Notations and Definitions ; 1.1 Notations ; 1.2 Definitions ; Chapter 2 Correlation and Dependence : An Introspection ; 2.1 Independence ; 2.2 Zero Correlation Versus Dependence ; 2.3 Some Geometrical Examples ; 2.4 Some Further Historical Remarks
2.5 A Brief Tour of Early Applications and Misinterpretations Chapter 3 Concepts of Dependence and Stochastic Ordering ; 3.1 Introduction ; 3.2 Concepts of Positive Dependence ; 3.3 Negative Dependence for More than Two Variables ; 3.4 Setwise Dependence ; 3.5 Other Approaches 3.6 Positive Dependence Orderings 3.7 Bayesian Approach to Stochastic Dependence ; Chapter 4 Copulas ; 4.1 Introduction ; 4.2 Definition and Some Properties ; 4.3 The Frechet Bounds ; 4.4 Examples ; 4.5 Construction of a Copula ; 4.6 Archimedean Copulas ; 4.7 Archimax Copulas 4.8 Copulas with Discontinuity Constraints 4.9 Copulas with More than Two Variables ; 4.10 Simulation Procedures ; Chapter 5 Farlie-Gumbel-Morgenstern Models of Dependence ; 5.1 Introduction ; 5.2 Initial Definition ; 5.3 Regression and Correlation ; 5.4 Iterations 5.5 Dependence Properties 5.6 A Class of n-variate FGM Distributions ; 5.7 Further Extensions ; 5.8 FGM Sequences ; Chapter 6 Global Versus Local Dependence between Random Variables ; 6.1 Introduction ; 6.2 Global Measures of Dependence ; 6.3 Local Indices of Dependence 6.4 Non-parametric Estimation of Local Indices |
Record Nr. | UNINA-9910809895503321 |
Mari Dominique Drouet | ||
London, : Imperial College Press | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Counting statistics for dependent random events : with a focus on finance / / Enrico Bernardi and Silvia Romagnoli |
Autore | Bernardi Enrico <1838-1900, > |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (213 pages) : illustrations |
Disciplina | 519.535 |
Soggetto topico |
Dependence (Statistics)
Copulas (Mathematical statistics) Finance - Mathematical models Dependència (Estadística) Finances Models matemàtics |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-64250-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- List of Common Symbols, Notations, and Acronyms -- Contents -- Part I The Main Ingredients -- 1 Clustering -- 1.1 Preliminary on Clustering -- 1.2 The Similarity Measure for Static Data -- 1.3 The Similarity Measure for Time Series -- 1.3.1 Model-Free Approaches -- 1.3.2 Model-Based Approaches -- 1.4 Hierarchical Algorithm -- 1.5 Partitioning Algorithm -- 1.5.1 k-Means Clustering -- 1.6 Neural Network Models -- 1.6.1 Clustering Algorithms -- 1.6.2 Kohonen Self-Organizing Maps -- 1.7 Search-Based Approaches -- 1.7.1 Evolutionary Approaches for Clustering -- 1.7.2 Simulated Annealing Approach -- 1.8 A Clustering Exercise on the European Banking System -- References -- 2 Copula Function and C-Volume -- 2.1 Copula Functions -- 2.1.1 Fréchet-Hoeffding Bounds of a n-Dimensional Copula and Association Measures -- 2.2 Families of Copulas -- 2.2.1 Elliptical Copulas -- Gaussian Copulas -- Student's t Copula -- 2.2.2 Archimedean Copulas -- 2.2.3 Extreme-Value Copulas -- 2.3 Pure Hierarchical Copulas -- 2.4 Hierarchical Grouping Copulas -- 2.4.1 Clusterized Homogeneous and Clusterized Hierarchical Copulas -- 2.4.2 Hierarchical Kendall Copulas -- 2.5 Volume of an n-Dimensional Copula -- 2.5.1 Clusterized Hierarchical Copulas: CHY-Volume -- 2.6 Example: Homogeneous CHY-Volume Versus CR Algorithm -- 2.6.1 Scalability of the Homogeneous CHY-Based Algorithm -- References -- 3 Combinatorics and Random Matrices: A Brief Review -- 3.1 Combinatoric Distribution of a Random Event -- 3.1.1 Permutations: Ordered Selection -- 3.1.2 Combinations: Unordered Selection -- 3.1.3 The Hardy-Ramanujan Asymptotic Partition Formula -- 3.1.4 The Combinatorial Problem in CHY-Volume Computation -- 3.1.5 Testing Compatibility with the Groups -- 3.2 Random Matrices -- 3.2.1 Gaussian Ensembles -- 3.2.2 An Illustrative Example of a Two-by-Two Random Matrix.
3.2.3 Singular Values of Rectangular Matrices -- 3.2.4 Marchenko-Pastur Distribution -- 3.2.5 The Distorted Combinatoric Distributions -- References -- Part II Mixing the Ingredients: A Recipe for a New Aggregation Algorithm -- 4 Counting a Random Event: Traditional Approach and New Perspectives -- 4.1 Counting Variables: Fundamentals in Literature -- 4.1.1 Generalized Poisson Distribution -- 4.1.2 Compound Poisson Distribution -- 4.2 Counting Process: Fundamentals in Literature -- 4.2.1 Counting Processes in Credit Risk Models: The Intensity-Based Approach -- 4.3 A New Combinatoric Approach for Counting -- 4.3.1 A Counting Variable Linked to a Clusterized Homogeneous Dependence Structure -- 4.3.2 Clusterized Homogeneous Copulas: CHC-Volume -- 4.3.3 Preparing the CHC-Computation -- 4.3.4 CHC and CHY Computation -- 4.3.5 The Volume of a Clusterized Copula: CHC and CHY -- 4.3.6 Pdf of a Counting Variable Linked to a CHC: A Formal Approach -- 4.3.7 The Boxes' Definition for the CHC-Volume Computation -- 4.3.8 The Dynamic Version of the Combinatoric-Approach -- References -- 5 A New Copula-Based Approach for Counting: The Distorted and the Limiting Case -- 5.1 The Distorted Copula-Based Approach: Fatal Event -- 5.1.1 From a Not Distorted to a Distorted Structure: A Probabilistic Discussion -- 5.1.2 Distorted Copula-Based Distribution of a Fatal Counting Variable -- 5.2 The Distorted Copula-Based Approach: Not Fatal Event -- 5.2.1 The Distorted Copula-Based Distribution of a Not Fatal Counting Variable -- 5.2.2 A Pseudo-Spectral Analysis of the Arrival Matrices -- 5.3 High-Dimensional Problems: The Pure Limiting Models -- 5.4 High-Dimensional Problems: The Limiting Clusterized Copulas -- 5.4.1 Hierarchical Limiting Model: A Credit Risk Application -- The Within Classes Computing Step -- The Between Classes Aggregation Step -- Case 1 -- Case 2 -- Case 3. 5.4.2 Hierarchical Hybrid Copulas: A Credit Risk Application -- 5.4.3 Check for the Groups' Cardinality: The HYC Model -- References -- 6 Real Data Empirical Applications -- 6.1 HYC-Based Model for a Worldwide Sovereign Debt Large Portfolio -- 6.2 Risk Evaluation Based on HYC Model: A Credit-Exposed European Investment Portfolio Analysis -- 6.2.1 Copula-Based Loss Distribution -- 6.2.2 Calibration of the Dependencies -- 6.2.3 HYC Model: Portfolio Application -- 6.2.4 HYC-VaR versus CM-VaR: an Empirical In-Sample Experiment -- Hypothesis -- CM Model -- HYC Model -- 6.3 Structural and Marginal Distortion in a Credit-Exposed Portfolio: a DHC Application -- 6.4 A Bayesian Analysis of the DHC Model -- 6.4.1 Multivariate Dependence Calibration -- 6.4.2 The Loss Function: Index Versus Replicating Portfolio -- 6.4.3 A Bayesian Analysis on the Residuals -- References -- References. |
Record Nr. | UNISA-996466544803316 |
Bernardi Enrico <1838-1900, > | ||
Cham, Switzerland : , : Springer, , [2021] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Counting statistics for dependent random events : with a focus on finance / / Enrico Bernardi and Silvia Romagnoli |
Autore | Bernardi Enrico <1838-1900, > |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (213 pages) : illustrations |
Disciplina | 519.535 |
Soggetto topico |
Dependence (Statistics)
Copulas (Mathematical statistics) Finance - Mathematical models Dependència (Estadística) Finances Models matemàtics |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-64250-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- List of Common Symbols, Notations, and Acronyms -- Contents -- Part I The Main Ingredients -- 1 Clustering -- 1.1 Preliminary on Clustering -- 1.2 The Similarity Measure for Static Data -- 1.3 The Similarity Measure for Time Series -- 1.3.1 Model-Free Approaches -- 1.3.2 Model-Based Approaches -- 1.4 Hierarchical Algorithm -- 1.5 Partitioning Algorithm -- 1.5.1 k-Means Clustering -- 1.6 Neural Network Models -- 1.6.1 Clustering Algorithms -- 1.6.2 Kohonen Self-Organizing Maps -- 1.7 Search-Based Approaches -- 1.7.1 Evolutionary Approaches for Clustering -- 1.7.2 Simulated Annealing Approach -- 1.8 A Clustering Exercise on the European Banking System -- References -- 2 Copula Function and C-Volume -- 2.1 Copula Functions -- 2.1.1 Fréchet-Hoeffding Bounds of a n-Dimensional Copula and Association Measures -- 2.2 Families of Copulas -- 2.2.1 Elliptical Copulas -- Gaussian Copulas -- Student's t Copula -- 2.2.2 Archimedean Copulas -- 2.2.3 Extreme-Value Copulas -- 2.3 Pure Hierarchical Copulas -- 2.4 Hierarchical Grouping Copulas -- 2.4.1 Clusterized Homogeneous and Clusterized Hierarchical Copulas -- 2.4.2 Hierarchical Kendall Copulas -- 2.5 Volume of an n-Dimensional Copula -- 2.5.1 Clusterized Hierarchical Copulas: CHY-Volume -- 2.6 Example: Homogeneous CHY-Volume Versus CR Algorithm -- 2.6.1 Scalability of the Homogeneous CHY-Based Algorithm -- References -- 3 Combinatorics and Random Matrices: A Brief Review -- 3.1 Combinatoric Distribution of a Random Event -- 3.1.1 Permutations: Ordered Selection -- 3.1.2 Combinations: Unordered Selection -- 3.1.3 The Hardy-Ramanujan Asymptotic Partition Formula -- 3.1.4 The Combinatorial Problem in CHY-Volume Computation -- 3.1.5 Testing Compatibility with the Groups -- 3.2 Random Matrices -- 3.2.1 Gaussian Ensembles -- 3.2.2 An Illustrative Example of a Two-by-Two Random Matrix.
3.2.3 Singular Values of Rectangular Matrices -- 3.2.4 Marchenko-Pastur Distribution -- 3.2.5 The Distorted Combinatoric Distributions -- References -- Part II Mixing the Ingredients: A Recipe for a New Aggregation Algorithm -- 4 Counting a Random Event: Traditional Approach and New Perspectives -- 4.1 Counting Variables: Fundamentals in Literature -- 4.1.1 Generalized Poisson Distribution -- 4.1.2 Compound Poisson Distribution -- 4.2 Counting Process: Fundamentals in Literature -- 4.2.1 Counting Processes in Credit Risk Models: The Intensity-Based Approach -- 4.3 A New Combinatoric Approach for Counting -- 4.3.1 A Counting Variable Linked to a Clusterized Homogeneous Dependence Structure -- 4.3.2 Clusterized Homogeneous Copulas: CHC-Volume -- 4.3.3 Preparing the CHC-Computation -- 4.3.4 CHC and CHY Computation -- 4.3.5 The Volume of a Clusterized Copula: CHC and CHY -- 4.3.6 Pdf of a Counting Variable Linked to a CHC: A Formal Approach -- 4.3.7 The Boxes' Definition for the CHC-Volume Computation -- 4.3.8 The Dynamic Version of the Combinatoric-Approach -- References -- 5 A New Copula-Based Approach for Counting: The Distorted and the Limiting Case -- 5.1 The Distorted Copula-Based Approach: Fatal Event -- 5.1.1 From a Not Distorted to a Distorted Structure: A Probabilistic Discussion -- 5.1.2 Distorted Copula-Based Distribution of a Fatal Counting Variable -- 5.2 The Distorted Copula-Based Approach: Not Fatal Event -- 5.2.1 The Distorted Copula-Based Distribution of a Not Fatal Counting Variable -- 5.2.2 A Pseudo-Spectral Analysis of the Arrival Matrices -- 5.3 High-Dimensional Problems: The Pure Limiting Models -- 5.4 High-Dimensional Problems: The Limiting Clusterized Copulas -- 5.4.1 Hierarchical Limiting Model: A Credit Risk Application -- The Within Classes Computing Step -- The Between Classes Aggregation Step -- Case 1 -- Case 2 -- Case 3. 5.4.2 Hierarchical Hybrid Copulas: A Credit Risk Application -- 5.4.3 Check for the Groups' Cardinality: The HYC Model -- References -- 6 Real Data Empirical Applications -- 6.1 HYC-Based Model for a Worldwide Sovereign Debt Large Portfolio -- 6.2 Risk Evaluation Based on HYC Model: A Credit-Exposed European Investment Portfolio Analysis -- 6.2.1 Copula-Based Loss Distribution -- 6.2.2 Calibration of the Dependencies -- 6.2.3 HYC Model: Portfolio Application -- 6.2.4 HYC-VaR versus CM-VaR: an Empirical In-Sample Experiment -- Hypothesis -- CM Model -- HYC Model -- 6.3 Structural and Marginal Distortion in a Credit-Exposed Portfolio: a DHC Application -- 6.4 A Bayesian Analysis of the DHC Model -- 6.4.1 Multivariate Dependence Calibration -- 6.4.2 The Loss Function: Index Versus Replicating Portfolio -- 6.4.3 A Bayesian Analysis on the Residuals -- References -- References. |
Record Nr. | UNINA-9910483919303321 |
Bernardi Enrico <1838-1900, > | ||
Cham, Switzerland : , : Springer, , [2021] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Dependence modeling |
Pubbl/distr/stampa | Warsaw, Poland : , : Versita, , 2013- |
Soggetto topico |
Dependence (Statistics)
Multivariate analysis Copulas (Mathematical statistics) |
Soggetto genere / forma | Periodicals. |
Soggetto non controllato | Mathematical Statistics |
ISSN | 2300-2298 |
Formato | Materiale a stampa |
Livello bibliografico | Periodico |
Lingua di pubblicazione | eng |
Altri titoli varianti | DeMo |
Record Nr. | UNISA-996321906503316 |
Warsaw, Poland : , : Versita, , 2013- | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Dependence modeling |
Pubbl/distr/stampa | Warsaw, Poland : , : Versita, , 2013- |
Soggetto topico |
Dependence (Statistics)
Multivariate analysis Copulas (Mathematical statistics) |
Soggetto genere / forma | Periodicals. |
ISSN | 2300-2298 |
Formato | Materiale a stampa |
Livello bibliografico | Periodico |
Lingua di pubblicazione | eng |
Altri titoli varianti | DeMo |
Record Nr. | UNINA-9910131766103321 |
Warsaw, Poland : , : Versita, , 2013- | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Dependence modeling [[electronic resource] ] : vine copula handbook / / editors, Dorota Kurowicka, Harry Joe |
Pubbl/distr/stampa | Hackensack, N.J., : World Scientific, 2011 |
Descrizione fisica | 1 online resource (368 p.) |
Disciplina | 519.5 |
Altri autori (Persone) |
KurowickaDorota
JoeHarry |
Soggetto topico |
Copulas (Mathematical statistics)
Dependence (Statistics) Distribution (Probability theory) |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-14441-7
9786613144416 981-4299-88-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Preface; Contents; 1. Introduction: Dependence Modeling D. Kurowicka; 2. Multivariate Copulae M. Fischer; 3. Vines Arise R. M. Cooke, H. Joe and K. Aas; 4. Sampling Count Variables with Specified Pearson Correlation: A Comparison between a Naive and a C-Vine Sampling Approach V. Erhardt and C. Czado; 5. Micro Correlations and Tail Dependence R. M. Cooke, C. Kousky and H. Joe; 6. The Copula Information Criterion and Its Implications for the Maximum Pseudo-Likelihood Estimator S. Grønneberg; 7. Dependence Comparisons of Vine Copulae with Four or More Variables H. Joe
8. Tail Dependence in Vine Copulae H. Joe9. Counting Vines O. Morales-Napoles; 10. Regular Vines: Generation Algorithm and Number of Equivalence Classes H. Joe, R. M. Cooke and D. Kurowicka; 11. Optimal Truncation of Vines D. Kurowicka; 12. Bayesian Inference for D-Vines: Estimation and Model Selection C. Czado and A. Min; 13. Analysis of Australian Electricity Loads Using Joint Bayesian Inference of D-Vines with Autoregressive Margins C. Czado, F. G ̈artner and A. Min; 14. Non-Parametric Bayesian Belief Nets versus Vines A. Hanea 15. Modeling Dependence between Financial Returns Using Pair-Copula Constructions K. Aas and D. Berg16. Dynamic D-Vine Model A. Heinen and A. Valdesogo; 17. Summary and Future Directions D. Kurowicka; Index |
Record Nr. | UNINA-9910463930303321 |
Hackensack, N.J., : World Scientific, 2011 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Dependence modeling [[electronic resource] ] : vine copula handbook / / editors, Dorota Kurowicka, Harry Joe |
Pubbl/distr/stampa | Hackensack, N.J., : World Scientific, 2011 |
Descrizione fisica | 1 online resource (368 p.) |
Disciplina | 519.5 |
Altri autori (Persone) |
KurowickaDorota
JoeHarry |
Soggetto topico |
Copulas (Mathematical statistics)
Dependence (Statistics) Distribution (Probability theory) |
ISBN |
1-283-14441-7
9786613144416 981-4299-88-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Preface; Contents; 1. Introduction: Dependence Modeling D. Kurowicka; 2. Multivariate Copulae M. Fischer; 3. Vines Arise R. M. Cooke, H. Joe and K. Aas; 4. Sampling Count Variables with Specified Pearson Correlation: A Comparison between a Naive and a C-Vine Sampling Approach V. Erhardt and C. Czado; 5. Micro Correlations and Tail Dependence R. M. Cooke, C. Kousky and H. Joe; 6. The Copula Information Criterion and Its Implications for the Maximum Pseudo-Likelihood Estimator S. Grønneberg; 7. Dependence Comparisons of Vine Copulae with Four or More Variables H. Joe
8. Tail Dependence in Vine Copulae H. Joe9. Counting Vines O. Morales-Napoles; 10. Regular Vines: Generation Algorithm and Number of Equivalence Classes H. Joe, R. M. Cooke and D. Kurowicka; 11. Optimal Truncation of Vines D. Kurowicka; 12. Bayesian Inference for D-Vines: Estimation and Model Selection C. Czado and A. Min; 13. Analysis of Australian Electricity Loads Using Joint Bayesian Inference of D-Vines with Autoregressive Margins C. Czado, F. G ̈artner and A. Min; 14. Non-Parametric Bayesian Belief Nets versus Vines A. Hanea 15. Modeling Dependence between Financial Returns Using Pair-Copula Constructions K. Aas and D. Berg16. Dynamic D-Vine Model A. Heinen and A. Valdesogo; 17. Summary and Future Directions D. Kurowicka; Index |
Record Nr. | UNINA-9910788555203321 |
Hackensack, N.J., : World Scientific, 2011 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|