Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock |
Autore | Deuschel, Jean-Dominique |
Pubbl/distr/stampa | Boston [etc.] : Academic Press, c1989 |
Descrizione fisica | xiv, 307 p. ; 24 cm |
Disciplina | 519.534 |
Collana | Pure and applied mathematics |
Soggetto non controllato |
Large deviations
Processi di markov |
ISBN | 0-12-213150-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-990001438060403321 |
Deuschel, Jean-Dominique
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Boston [etc.] : Academic Press, c1989 | ||
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Lo trovi qui: Univ. Federico II | ||
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Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock |
Autore | Deuschel, Jean-Dominique |
Pubbl/distr/stampa | Providence, R.I. : AMS Chelsea Publ., c1989 |
Descrizione fisica | xii, 283 p. ; 24 cm |
Disciplina | 519.534 |
Altri autori (Persone) | Stroock, Daniel W. |
Soggetto topico | Large deviations |
ISBN | 082182757X |
Classificazione |
AMS 28D05
AMS 28D20 AMS 60F10 AMS 60F17 LC QA273.67.D48 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991003686639707536 |
Deuschel, Jean-Dominique
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Providence, R.I. : AMS Chelsea Publ., c1989 | ||
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Lo trovi qui: Univ. del Salento | ||
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Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock |
Autore | Deuschel, Jean-Dominique <1957- > |
Pubbl/distr/stampa | Boston : Academic Press, c1989 |
Descrizione fisica | xiv, 307 p. ; 24 cm |
Disciplina | 519.534 |
Altri autori (Persone) | Stroock, Daniel W. |
Collana | Pure and applied mathematics ; 137 |
Soggetto topico | Statistica - Metodi matematici |
ISBN | 0122131509 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | und |
Record Nr. | UNISALENTO-991002927829707536 |
Deuschel, Jean-Dominique <1957- >
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Boston : Academic Press, c1989 | ||
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Lo trovi qui: Univ. del Salento | ||
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Large deviations / Frank den Hollander |
Autore | Hollander, Frank den |
Pubbl/distr/stampa | Providence, R. I. : American Mathematical Society, c2000 |
Descrizione fisica | x, 143 p. : ill. ; 27 cm |
Disciplina | 519.534 |
Collana | Fields Institute monographs, 1069-5273 ; 14 |
Soggetto topico | Large deviations |
ISBN | 0821819895 |
Classificazione |
AMS 60F10
LC QA273.67.H65 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991000283969707536 |
Hollander, Frank den
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Providence, R. I. : American Mathematical Society, c2000 | ||
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Lo trovi qui: Univ. del Salento | ||
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Large deviations and idempotent probability / A. Puhalskii |
Autore | Puhalskii, Anatolii |
Pubbl/distr/stampa | Boca Raton : Chapman & Hall/CRC, c2001 |
Descrizione fisica | ix, 500 p. ; 24 cm |
Disciplina | 519.534 |
Collana | Chapman & Hall/CRC monographs and surveys in pure and applied mathematics |
Soggetto non controllato |
Teoria della probabilità e processi stocastici
Probabilità - Misura |
ISBN | 1-58488-198-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-990001488240403321 |
Puhalskii, Anatolii
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Boca Raton : Chapman & Hall/CRC, c2001 | ||
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Lo trovi qui: Univ. Federico II | ||
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Large deviations and metastability / Enzo Olivieri, Maria Eulália Vares |
Autore | Olivieri, Enzo |
Pubbl/distr/stampa | Cambridge ; New York : Cambridge University Press, 2005 |
Descrizione fisica | xv, 512 p. : ill., 24 cm |
Disciplina | 519.534 |
Altri autori (Persone) | Vares, Maria Euláliaauthor |
Collana | Encyclopedia of mathematics and its applications ; 100 |
Soggetto topico |
Large deviations
Stability |
ISBN | 0521591635 |
Classificazione |
AMS 60F10
LC QA273.67.O45 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991000915539707536 |
Olivieri, Enzo
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Cambridge ; New York : Cambridge University Press, 2005 | ||
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Lo trovi qui: Univ. del Salento | ||
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Large deviations techniques and applications / Amir Dembo, Ofer Zeitouni |
Autore | Dembo, Amir |
Pubbl/distr/stampa | Boston : Jones and Bartlett, c1993 |
Descrizione fisica | xiii, 346 p. : ill. ; 24 cm |
Disciplina | 519.534 |
Altri autori (Persone) | Zeitouni, Oferauthor |
Collana | Jones and Bartlett books in mathematics |
Soggetto topico | Probabilità - Teoria |
ISBN | 0867202912 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991002916299707536 |
Dembo, Amir
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Boston : Jones and Bartlett, c1993 | ||
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Lo trovi qui: Univ. del Salento | ||
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A weak convergence approach to the theory of large deviations [[electronic resource] /] / Paul Dupuis, Richard S. Ellis |
Autore | Dupuis Paul |
Pubbl/distr/stampa | New York, : Wiley, c1997 |
Descrizione fisica | 1 online resource (506 p.) |
Disciplina | 519.534 |
Altri autori (Persone) | EllisRichard S <1947-> (Richard Steven) |
Collana | Wiley series in probability and statistics. Probability and statistics |
Soggetto topico |
Convergence
Large deviations |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-27400-0
9786613274007 1-118-16590-X 1-118-16589-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
A Weak Convergence Approach to the Theory of Large Deviations; Preface; Contents; 1. Formulation of Large Deviation Theory in Terms of the Laplace Principle; 1.1. Introduction; 1.2. Equivalent Formulation of the Large Deviation Principle; 1.3. Basic Results in the Theory; 1.4. Properties of the Relative Entropy; 1.5. Stochastic Control Theory and Dynamic Programming; 2. First Example: Sanov's Theorem; 2.1. Introduction; 2.2. Statement of Sanov's Theorem; 2.3. The Representation Formula; 2.4. Proof of the Laplace Principle Lower Bound; 2.5. Proof of the Laplace Principle Upper Bound
3. Second Example: Mogulskii's Theorem3.1. Introduction; 3.2. The Representation Formula; 3.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 3.4. Statement of Mogulskii's Theorem and Completion of the Proof; 3.5. Cramér's Theorem; 3.6. Comments on the Proofs; 4 Representation Formulas for Other Stochastic Processes; 4.1. Introduction; 4.2. The Representation Formula for the Empirical Measures of a Markov Chain; 4.3. The Representation Formula for a Random Walk Model; 4.4. The Representation Formula for a Random Walk Model with State-Dependent Noise 4.5. Extensions to Unbounded Functions4.6. Representation Formulas for Continuous-Time Markov Processes; 4.6.1. Introduction; 4.6.2. Formal Derivation of Representation Formulas for Continuous-Time Markov Processes; 4.6.3. Examples of Continuous-Time Representation Formulas; 4.6.4. Remarks on the Proofs of the Representation Formulas; 5 Compactness and Limit Properties for the Random Walk Model; 5.1. Introduction; 5.2. Definitions and a Representation Formula; 5.3. Compactness and Limit Properties; 5.4. Weaker Version of Condition 5.3.1 6 Laplace Principle for the Random Walk Model with Continuous Statistics6.1. Introduction; 6.2. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 6.3. Statement of the Laplace Principle; 6.4. Strategy for the Proof of the Laplace Principle Lower Bound; 6.5. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.1; 6.6. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.2; 6.7. Extension of Theorem 6.3.3 To Be Applied in Chapter 10; 7. Laplace Principle for the Random Walk Model with Discontinuous Statistics 7.1. Introduction7.2. Statement of the Laplace Principle; 7.3. Laplace Principle for the Final Position Vectors and One-Dimensional Examples; 7.4. Proof of the Laplace Principle Upper Bound; 7.5. Proof of the Laplace Principle Lower Bound; 7.6. Compactness of the Level Sets of Ix; 8. Laplace Principle for the Empirical Measures of a Markov Chain; 8.1. Introduction; 8.2. Compactness and Limit Properties of Controls and Controlled Processes; 8.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 8.4. Statement of the Laplace Principle 8.5. Properties of the Rate Function |
Record Nr. | UNINA-9910139594403321 |
Dupuis Paul
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New York, : Wiley, c1997 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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A weak convergence approach to the theory of large deviations [[electronic resource] /] / Paul Dupuis, Richard S. Ellis |
Autore | Dupuis Paul |
Pubbl/distr/stampa | New York, : Wiley, c1997 |
Descrizione fisica | 1 online resource (506 p.) |
Disciplina | 519.534 |
Altri autori (Persone) | EllisRichard S <1947-> (Richard Steven) |
Collana | Wiley series in probability and statistics. Probability and statistics |
Soggetto topico |
Convergence
Large deviations |
ISBN |
1-283-27400-0
9786613274007 1-118-16590-X 1-118-16589-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
A Weak Convergence Approach to the Theory of Large Deviations; Preface; Contents; 1. Formulation of Large Deviation Theory in Terms of the Laplace Principle; 1.1. Introduction; 1.2. Equivalent Formulation of the Large Deviation Principle; 1.3. Basic Results in the Theory; 1.4. Properties of the Relative Entropy; 1.5. Stochastic Control Theory and Dynamic Programming; 2. First Example: Sanov's Theorem; 2.1. Introduction; 2.2. Statement of Sanov's Theorem; 2.3. The Representation Formula; 2.4. Proof of the Laplace Principle Lower Bound; 2.5. Proof of the Laplace Principle Upper Bound
3. Second Example: Mogulskii's Theorem3.1. Introduction; 3.2. The Representation Formula; 3.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 3.4. Statement of Mogulskii's Theorem and Completion of the Proof; 3.5. Cramér's Theorem; 3.6. Comments on the Proofs; 4 Representation Formulas for Other Stochastic Processes; 4.1. Introduction; 4.2. The Representation Formula for the Empirical Measures of a Markov Chain; 4.3. The Representation Formula for a Random Walk Model; 4.4. The Representation Formula for a Random Walk Model with State-Dependent Noise 4.5. Extensions to Unbounded Functions4.6. Representation Formulas for Continuous-Time Markov Processes; 4.6.1. Introduction; 4.6.2. Formal Derivation of Representation Formulas for Continuous-Time Markov Processes; 4.6.3. Examples of Continuous-Time Representation Formulas; 4.6.4. Remarks on the Proofs of the Representation Formulas; 5 Compactness and Limit Properties for the Random Walk Model; 5.1. Introduction; 5.2. Definitions and a Representation Formula; 5.3. Compactness and Limit Properties; 5.4. Weaker Version of Condition 5.3.1 6 Laplace Principle for the Random Walk Model with Continuous Statistics6.1. Introduction; 6.2. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 6.3. Statement of the Laplace Principle; 6.4. Strategy for the Proof of the Laplace Principle Lower Bound; 6.5. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.1; 6.6. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.2; 6.7. Extension of Theorem 6.3.3 To Be Applied in Chapter 10; 7. Laplace Principle for the Random Walk Model with Discontinuous Statistics 7.1. Introduction7.2. Statement of the Laplace Principle; 7.3. Laplace Principle for the Final Position Vectors and One-Dimensional Examples; 7.4. Proof of the Laplace Principle Upper Bound; 7.5. Proof of the Laplace Principle Lower Bound; 7.6. Compactness of the Level Sets of Ix; 8. Laplace Principle for the Empirical Measures of a Markov Chain; 8.1. Introduction; 8.2. Compactness and Limit Properties of Controls and Controlled Processes; 8.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 8.4. Statement of the Laplace Principle 8.5. Properties of the Rate Function |
Record Nr. | UNINA-9910830133003321 |
Dupuis Paul
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||
New York, : Wiley, c1997 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
A weak convergence approach to the theory of large deviations [[electronic resource] /] / Paul Dupuis, Richard S. Ellis |
Autore | Dupuis Paul |
Pubbl/distr/stampa | New York, : Wiley, c1997 |
Descrizione fisica | 1 online resource (506 p.) |
Disciplina | 519.534 |
Altri autori (Persone) | EllisRichard S <1947-> (Richard Steven) |
Collana | Wiley series in probability and statistics. Probability and statistics |
Soggetto topico |
Convergence
Large deviations |
ISBN |
1-283-27400-0
9786613274007 1-118-16590-X 1-118-16589-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
A Weak Convergence Approach to the Theory of Large Deviations; Preface; Contents; 1. Formulation of Large Deviation Theory in Terms of the Laplace Principle; 1.1. Introduction; 1.2. Equivalent Formulation of the Large Deviation Principle; 1.3. Basic Results in the Theory; 1.4. Properties of the Relative Entropy; 1.5. Stochastic Control Theory and Dynamic Programming; 2. First Example: Sanov's Theorem; 2.1. Introduction; 2.2. Statement of Sanov's Theorem; 2.3. The Representation Formula; 2.4. Proof of the Laplace Principle Lower Bound; 2.5. Proof of the Laplace Principle Upper Bound
3. Second Example: Mogulskii's Theorem3.1. Introduction; 3.2. The Representation Formula; 3.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 3.4. Statement of Mogulskii's Theorem and Completion of the Proof; 3.5. Cramér's Theorem; 3.6. Comments on the Proofs; 4 Representation Formulas for Other Stochastic Processes; 4.1. Introduction; 4.2. The Representation Formula for the Empirical Measures of a Markov Chain; 4.3. The Representation Formula for a Random Walk Model; 4.4. The Representation Formula for a Random Walk Model with State-Dependent Noise 4.5. Extensions to Unbounded Functions4.6. Representation Formulas for Continuous-Time Markov Processes; 4.6.1. Introduction; 4.6.2. Formal Derivation of Representation Formulas for Continuous-Time Markov Processes; 4.6.3. Examples of Continuous-Time Representation Formulas; 4.6.4. Remarks on the Proofs of the Representation Formulas; 5 Compactness and Limit Properties for the Random Walk Model; 5.1. Introduction; 5.2. Definitions and a Representation Formula; 5.3. Compactness and Limit Properties; 5.4. Weaker Version of Condition 5.3.1 6 Laplace Principle for the Random Walk Model with Continuous Statistics6.1. Introduction; 6.2. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 6.3. Statement of the Laplace Principle; 6.4. Strategy for the Proof of the Laplace Principle Lower Bound; 6.5. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.1; 6.6. Proof of the Laplace Principle Lower Bound Under Conditions 6.2.1 and 6.3.2; 6.7. Extension of Theorem 6.3.3 To Be Applied in Chapter 10; 7. Laplace Principle for the Random Walk Model with Discontinuous Statistics 7.1. Introduction7.2. Statement of the Laplace Principle; 7.3. Laplace Principle for the Final Position Vectors and One-Dimensional Examples; 7.4. Proof of the Laplace Principle Upper Bound; 7.5. Proof of the Laplace Principle Lower Bound; 7.6. Compactness of the Level Sets of Ix; 8. Laplace Principle for the Empirical Measures of a Markov Chain; 8.1. Introduction; 8.2. Compactness and Limit Properties of Controls and Controlled Processes; 8.3. Proof of the Laplace Principle Upper Bound and Identification of the Rate Function; 8.4. Statement of the Laplace Principle 8.5. Properties of the Rate Function |
Record Nr. | UNINA-9910841896703321 |
Dupuis Paul
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New York, : Wiley, c1997 | ||
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Lo trovi qui: Univ. Federico II | ||
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