Ecole d'eté de probabilités de Saint-Flour XIX - 1989 [e-book] / by Donald L. Burkholder, Etienne Pardoux, Alain-Sol Sznitman ; edited by Paul-Louis Hennequin |
Autore | Burkholder, Donald L. |
Pubbl/distr/stampa | Berlin : Springer, 1991 |
Descrizione fisica | 1 online resource (vi, 259 p.) |
Disciplina | 519.2 |
Altri autori (Persone) |
Pardoux, Etienneauthor
Sznitman, Alain-Sol Hennequin, Paul-Louis |
Collana | Lecture Notes in Mathematics, 0075-8434 ; 1464 |
Soggetto topico |
Mathematics
Global analysis (Mathematics) Distribution (Probability theory) |
ISBN | 9783540463191 |
Classificazione |
AMS 60G
AMS 60H AMS 60J |
Formato | Risorse elettroniche |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991002228739707536 |
Burkholder, Donald L. | ||
Berlin : Springer, 1991 | ||
Risorse elettroniche | ||
Lo trovi qui: Univ. del Salento | ||
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Ecole d'été de probabilités de Saint-Flour XIX-1989 / D. L. Burkholder, E. Pardoux, A. Sznitman ; editor P. L. Hennequin |
Autore | Burkholder, Donald L. |
Pubbl/distr/stampa | Berlin : Springer-Verlag, 1991 |
Descrizione fisica | vi, 259 p. ; 24 cm. |
Disciplina | 519.2 |
Altri autori (Persone) |
Pardoux, Etienneauthor
Sznitman, Alain-Sol Hennequin, Paul Louis |
Altri autori (Convegni) | Ecole d'été de probabilités de Saint-Flour <19. ; 1989> |
Collana | Lecture notes in mathematics, 0075-8434 ; 1464 |
Soggetto topico | Probability theory |
ISBN | 3540538410 |
Classificazione |
AMS 31A05
AMS 35R60 AMS 60-02 AMS 60G35 AMS 60G46 AMS 60J65 AMS 60K35 AMS 62M20 AMS 70-02 AMS 82-02 AMS 82A31 (1985) |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | fre |
Record Nr. | UNISALENTO-991000840879707536 |
Burkholder, Donald L. | ||
Berlin : Springer-Verlag, 1991 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. del Salento | ||
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Introduction to Monte-Carlo methods for transport and diffusion equations / B. Lapeyre, É. Pardoux, R. Sentis ; translated by Alan Craig and Fionn Craig |
Autore | Lapeyre, Bernard |
Pubbl/distr/stampa | Oxford : Oxford University Press, c2003 |
Descrizione fisica | ix, 163 p. ; 24 cm |
Disciplina | 519.2 |
Altri autori (Persone) |
Pardoux, Étienne
Sentis, Rémi |
Collana | Oxford texts in applied and engineering mathematics |
Soggetto non controllato |
Statistica computazionale
Metodo Monte Carlo |
ISBN | 0-19-852593-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-990007905410403321 |
Lapeyre, Bernard | ||
Oxford : Oxford University Press, c2003 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Introduction to Monte-Carlo methods for transport and diffusion equations / Bernard Lapeyre, Etienne Pardoux, Remi Sentis ; Translated By Alan Craig and Fionn Craig |
Autore | Lapeyre, Bernard |
Edizione | [1. rist] |
Pubbl/distr/stampa | Oxford, : Oxford University Press, 2003 |
Descrizione fisica | IX, 163 p. ; 24 cm |
Disciplina | 519.282 |
Altri autori (Persone) |
Sentis, Remi
Pardoux, Etienne |
Collana | Oxford texts in applied and engineering mathematics. - Oxford |
Soggetto topico | Probabilita |
ISBN | 0198525923 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAS-RML0293839 |
Lapeyre, Bernard | ||
Oxford, : Oxford University Press, 2003 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Cassino | ||
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Markov processes and applications [[electronic resource] ] : algorithms, networks, genome and finance / / Etienne Pardoux |
Autore | Pardoux E (Etienne), <1947-> |
Pubbl/distr/stampa | Chichester, U.K., : Wiley/Dunod, 2008 |
Descrizione fisica | 1 online resource (323 p.) |
Disciplina | 519.2/33 |
Collana |
Wiley series in probability and statistics
Wiley-Dunod series |
Soggetto topico | Markov processes |
ISBN |
0-470-72187-1
1-282-34278-9 9786612342783 0-470-72186-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Markov Processes and Applications; Contents; Preface; 1 Simulations and the Monte Carlo method; 1.1 Description of the method; 1.2 Convergence theorems; 1.3 Simulation of random variables; 1.4 Variance reduction techniques; 1.5 Exercises; 2 Markov chains; 2.1 Definitions and elementary properties; 2.2 Examples; 2.2.1 Random walk in E = Zd; 2.2.2 Bienaym ́e-Galton-Watson process; 2.2.3 A discrete time queue; 2.3 Strong Markov property; 2.4 Recurrent and transient states; 2.5 The irreducible and recurrent case; 2.6 The aperiodic case; 2.7 Reversible Markov chain
2.8 Rate of convergence to equilibrium2.8.1 The reversible finite state case; 2.8.2 The general case; 2.9 Statistics of Markov chains; 2.10 Exercises; 3 Stochastic algorithms; 3.1 Markov chain Monte Carlo; 3.1.1 An application; 3.1.2 The Ising model; 3.1.3 Bayesian analysis of images; 3.1.4 Heated chains; 3.2 Simulation of the invariant probability; 3.2.1 Perfect simulation; 3.2.2 Coupling from the past; 3.3 Rate of convergence towards the invariant probability; 3.4 Simulated annealing; 3.5 Exercises; 4 Markov chains and the genome; 4.1 Reading DNA; 4.1.1 CpG islands 4.1.2 Detection of the genes in a prokaryotic genome4.2 The i.i.d. model; 4.3 The Markov model; 4.3.1 Application to CpG islands; 4.3.2 Search for genes in a prokaryotic genome; 4.3.3 Statistics of Markov chains Mk; 4.3.4 Phased Markov chains; 4.3.5 Locally homogeneous Markov chains; 4.4 Hidden Markov models; 4.4.1 Computation of the likelihood; 4.4.2 The Viterbi algorithm; 4.4.3 Parameter estimation; 4.5 Hidden semi-Markov model; 4.5.1 Limitations of the hidden Markov model; 4.5.2 What is a semi-Markov chain?; 4.5.3 The hidden semi-Markov model; 4.5.4 The semi-Markov Viterbi algorithm 4.5.5 Search for genes in a prokaryotic genome4.6 Alignment of two sequences; 4.6.1 The Needleman-Wunsch algorithm; 4.6.2 Hidden Markov model alignment algorithm; 4.6.3 A posteriori probability distribution of the alignment; 4.6.4 A posteriori probability of a given match; 4.7 A multiple alignment algorithm; 4.8 Exercises; 5 Control and filtering of Markov chains; 5.1 Deterministic optimal control; 5.2 Control of Markov chains; 5.3 Linear quadratic optimal control; 5.4 Filtering of Markov chains; 5.5 The Kalman-Bucy filter; 5.5.1 Motivation; 5.5.2 Solution of the filtering problem 5.6 Linear-quadratic control with partial observation5.7 Exercises; 6 The Poisson process; 6.1 Point processes and counting processes; 6.2 The Poisson process; 6.3 The Markov property; 6.4 Large time behaviour; 6.5 Exercises; 7 Jump Markov processes; 7.1 General facts; 7.2 Infinitesimal generator; 7.3 The strong Markov property; 7.4 Embedded Markov chain; 7.5 Recurrent and transient states; 7.6 The irreducible recurrent case; 7.7 Reversibility; 7.8 Markov models of evolution and phylogeny; 7.8.1 Models of evolution; 7.8.2 Likelihood methods in phylogeny 7.8.3 The Bayesian approach to phylogeny |
Record Nr. | UNINA-9910144408003321 |
Pardoux E (Etienne), <1947-> | ||
Chichester, U.K., : Wiley/Dunod, 2008 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Markov processes and applications [[electronic resource] ] : algorithms, networks, genome and finance / / Etienne Pardoux |
Autore | Pardoux E (Etienne), <1947-> |
Pubbl/distr/stampa | Chichester, U.K., : Wiley/Dunod, 2008 |
Descrizione fisica | 1 online resource (323 p.) |
Disciplina | 519.2/33 |
Collana |
Wiley series in probability and statistics
Wiley-Dunod series |
Soggetto topico | Markov processes |
ISBN |
0-470-72187-1
1-282-34278-9 9786612342783 0-470-72186-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Markov Processes and Applications; Contents; Preface; 1 Simulations and the Monte Carlo method; 1.1 Description of the method; 1.2 Convergence theorems; 1.3 Simulation of random variables; 1.4 Variance reduction techniques; 1.5 Exercises; 2 Markov chains; 2.1 Definitions and elementary properties; 2.2 Examples; 2.2.1 Random walk in E = Zd; 2.2.2 Bienaym ́e-Galton-Watson process; 2.2.3 A discrete time queue; 2.3 Strong Markov property; 2.4 Recurrent and transient states; 2.5 The irreducible and recurrent case; 2.6 The aperiodic case; 2.7 Reversible Markov chain
2.8 Rate of convergence to equilibrium2.8.1 The reversible finite state case; 2.8.2 The general case; 2.9 Statistics of Markov chains; 2.10 Exercises; 3 Stochastic algorithms; 3.1 Markov chain Monte Carlo; 3.1.1 An application; 3.1.2 The Ising model; 3.1.3 Bayesian analysis of images; 3.1.4 Heated chains; 3.2 Simulation of the invariant probability; 3.2.1 Perfect simulation; 3.2.2 Coupling from the past; 3.3 Rate of convergence towards the invariant probability; 3.4 Simulated annealing; 3.5 Exercises; 4 Markov chains and the genome; 4.1 Reading DNA; 4.1.1 CpG islands 4.1.2 Detection of the genes in a prokaryotic genome4.2 The i.i.d. model; 4.3 The Markov model; 4.3.1 Application to CpG islands; 4.3.2 Search for genes in a prokaryotic genome; 4.3.3 Statistics of Markov chains Mk; 4.3.4 Phased Markov chains; 4.3.5 Locally homogeneous Markov chains; 4.4 Hidden Markov models; 4.4.1 Computation of the likelihood; 4.4.2 The Viterbi algorithm; 4.4.3 Parameter estimation; 4.5 Hidden semi-Markov model; 4.5.1 Limitations of the hidden Markov model; 4.5.2 What is a semi-Markov chain?; 4.5.3 The hidden semi-Markov model; 4.5.4 The semi-Markov Viterbi algorithm 4.5.5 Search for genes in a prokaryotic genome4.6 Alignment of two sequences; 4.6.1 The Needleman-Wunsch algorithm; 4.6.2 Hidden Markov model alignment algorithm; 4.6.3 A posteriori probability distribution of the alignment; 4.6.4 A posteriori probability of a given match; 4.7 A multiple alignment algorithm; 4.8 Exercises; 5 Control and filtering of Markov chains; 5.1 Deterministic optimal control; 5.2 Control of Markov chains; 5.3 Linear quadratic optimal control; 5.4 Filtering of Markov chains; 5.5 The Kalman-Bucy filter; 5.5.1 Motivation; 5.5.2 Solution of the filtering problem 5.6 Linear-quadratic control with partial observation5.7 Exercises; 6 The Poisson process; 6.1 Point processes and counting processes; 6.2 The Poisson process; 6.3 The Markov property; 6.4 Large time behaviour; 6.5 Exercises; 7 Jump Markov processes; 7.1 General facts; 7.2 Infinitesimal generator; 7.3 The strong Markov property; 7.4 Embedded Markov chain; 7.5 Recurrent and transient states; 7.6 The irreducible recurrent case; 7.7 Reversibility; 7.8 Markov models of evolution and phylogeny; 7.8.1 Models of evolution; 7.8.2 Likelihood methods in phylogeny 7.8.3 The Bayesian approach to phylogeny |
Record Nr. | UNINA-9910829101303321 |
Pardoux E (Etienne), <1947-> | ||
Chichester, U.K., : Wiley/Dunod, 2008 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Markov processes and applications : algorithms, networks, genome and finance / Etienne Pardoux |
Autore | Pardoux, Etienne |
Pubbl/distr/stampa | Chichester, : Wiley, : Dunod, 2008 |
Descrizione fisica | XII, 296 p. ; 23 cm |
Disciplina | 519.2 |
Collana | Wiley series in probability and statistics |
ISBN | 9780470772713 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISANNIO-PAV0000794 |
Pardoux, Etienne | ||
Chichester, : Wiley, : Dunod, 2008 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. del Sannio | ||
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Probabilistic Models of Population Evolution [[electronic resource] ] : Scaling Limits, Genealogies and Interactions / / by Étienne Pardoux |
Autore | Pardoux Étienne |
Edizione | [1st ed. 2016.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
Descrizione fisica | 1 online resource (VIII, 125 p. 6 illus., 2 illus. in color.) |
Disciplina | 519.234 |
Collana | Stochastics in Biological Systems |
Soggetto topico |
Biomathematics
Probabilities Ecology Mathematical and Computational Biology Probability Theory and Stochastic Processes Theoretical Ecology/Statistics |
ISBN | 3-319-30328-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction -- Branching Processes -- Convergence to a Continuous State Branching Process -- Continuous State Branching Process (CSBP) -- Genealogies -- Models of Finite Population with Interaction -- Convergence to a Continuous State Model -- Continuous Model with Interaction -- Appendix. |
Record Nr. | UNINA-9910254097303321 |
Pardoux Étienne | ||
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Probabilistic models of population evolution : scaling limits, genealogies and interactions / Etienne Pardoux |
Autore | Pardoux, Etienne |
Pubbl/distr/stampa | [Cham], : Springer, : Mathematical Biosciences Institute, 2016 |
Descrizione fisica | VIII, 125 p. : ill. ; 24 cm |
Soggetto topico |
60J80 - Branching processes (Galton-Watson, birth-and-death, etc.) [MSC 2020]
60H10 - Stochastic ordinary differential equations [MSC 2020] 92D25 - Population dynamics (general) [MSC 2020] 60J85 - Applications of branching processes [MSC 2020] 60F17 - Functional limit theorems; invariance principles [MSC 2020] |
Soggetto non controllato |
Bienaymé-Galton-Watson Processes
Continuous state branching processes Evolutionary Models Markov Chains Population models Populations with Interactions |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0115275 |
Pardoux, Etienne | ||
[Cham], : Springer, : Mathematical Biosciences Institute, 2016 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
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Probabilistic models of population evolution : scaling limits, genealogies and interactions / Etienne Pardoux |
Autore | Pardoux, Etienne |
Edizione | [[Cham] : Springer : Mathematical Biosciences Institute, 2016] |
Pubbl/distr/stampa | VIII, 125 p., : ill. ; 24 cm |
Descrizione fisica | Pubblicazione in formato elettronico |
Soggetto topico |
60J80 - Branching processes (Galton-Watson, birth-and-death, etc.) [MSC 2020]
60H10 - Stochastic ordinary differential equations [MSC 2020] 92D25 - Population dynamics (general) [MSC 2020] 60J85 - Applications of branching processes [MSC 2020] 60F17 - Functional limit theorems; invariance principles [MSC 2020] |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAMPANIA-SUN0115275 |
Pardoux, Etienne | ||
VIII, 125 p., : ill. ; 24 cm | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
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