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Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock
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  
Boston [etc.] : Academic Press, c1989
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock
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  
Providence, R.I. : AMS Chelsea Publ., c1989
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Large deviations / Jean-Dominique Deuschel, Daniel W. Stroock
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- >  
Boston : Academic Press, c1989
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Large deviations / Frank den Hollander
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  
Providence, R. I. : American Mathematical Society, c2000
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Large deviations and idempotent probability / A. Puhalskii
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  
Boca Raton : Chapman & Hall/CRC, c2001
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Large deviations and metastability / Enzo Olivieri, Maria Eulália Vares
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  
Cambridge ; New York : Cambridge University Press, 2005
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Large deviations techniques and applications / Amir Dembo, Ofer Zeitouni
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  
Boston : Jones and Bartlett, c1993
Materiale a stampa
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
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  
New York, : Wiley, c1997
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
A weak convergence approach to the theory of large deviations [[electronic resource] /] / Paul Dupuis, Richard S. Ellis
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  
New York, : Wiley, c1997
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
A weak convergence approach to the theory of large deviations [[electronic resource] /] / Paul Dupuis, Richard S. Ellis
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  
New York, : Wiley, c1997
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui