The Workshop on Stable Processes and Related Topics took place at Cor nell University in January 9-13, 1990, under the sponsorship of the Mathemat ical Sciences Institute. It attracted an international roster of probabilists from Brazil, Japan, Korea, Poland, Germany, Holland and France as well as the U. S. This volume contains a sample of the papers presented at the Workshop. All the papers have been refereed. Gaussian processes have been studied extensively over the last fifty years and form the bedrock of stochastic modeling. Their importance stems from the Central Limit Theorem. They share a number of special properties which facilitates their analysis and makes them particularly suitable to statistical inference. The many properties they share, however, is also the seed of their limitations. What happens in the real world away from the ideal Gaussian model? The non-Gaussian world may contain random processes that are close to the Gaussian. What are appropriate classes of nearly Gaussian models and how typical or robust is the Gaussian model amongst them? Moving further away from normality, what are appropriate non-Gaussian models that are sufficiently different to encompass distinct behavior, yet sufficiently simple to be amenable to efficient statistical inference? The very Central Limit Theorem which provides the fundamental justifi cation for approximate normality, points to stable and other infinitely divisible models. Some of these may be close to and others very different from Gaussian models.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Gaussian measures of large balls in ?n.- On a Class of Infinitely Divisible Processes Represented as Mixtures of Gaussian Processes.- Capacities, Large Deviations and Loglog Laws.- Conditional variance of symmetric stable variables.- Bounded Stationary Stable Processes and Entropy.- Alternative multivariate stable distributions and their applications to financial modeling.- Construction of Multiple Stable Measures and Integrals Using LePage Representation.- Numerical computation of non-linear stable regression functions.- A Characterization of the Asymptotic Behavior of Stationary Stable Processes.- An Extremal Problem in Hp of the Upper Half Plane with Application to Prediction of Stochastic Processes.- On Multiple Markov S?S Processes.- On shot noise processes attracted to fractional Lévy motion.- Self-similar Stable Processes with Stationary Increments.- A Stochastic Integral Representation for the Bootstrap of the Sample Mean.- Multiple stable integrals appearing in weak limits.- Characterizations of ergodic stationary stable processes via the dynamical functional.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Questo è un articolo print on demand. Codice articolo KGQI4VKNE9
Quantità: Più di 20 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781468467802_new
Quantità: Più di 20 disponibili
Da: Chiron Media, Wallingford, Regno Unito
Paperback. Condizione: New. Codice articolo 6666-IUK-9781468467802
Quantità: 10 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Workshop on Stable Processes and Related Topics took place at Cor nell University in January 9-13, 1990, under the sponsorship of the Mathemat ical Sciences Institute. It attracted an international roster of probabilists from Brazil, Japan, Korea, Poland, Germany, Holland and France as well as the U. S. This volume contains a sample of the papers presented at the Workshop. All the papers have been refereed. Gaussian processes have been studied extensively over the last fifty years and form the bedrock of stochastic modeling. Their importance stems from the Central Limit Theorem. They share a number of special properties which facilitates their analysis and makes them particularly suitable to statistical inference. The many properties they share, however, is also the seed of their limitations. What happens in the real world away from the ideal Gaussian model The non-Gaussian world may contain random processes that are close to the Gaussian. What are appropriate classes of nearly Gaussian models and how typical or robust is the Gaussian model amongst them Moving further away from normality, what are appropriate non-Gaussian models that are sufficiently different to encompass distinct behavior, yet sufficiently simple to be amenable to efficient statistical inference The very Central Limit Theorem which provides the fundamental justifi cation for approximate normality, points to stable and other infinitely divisible models. Some of these may be close to and others very different from Gaussian models. 340 pp. Englisch. Codice articolo 9781468467802
Quantità: 2 disponibili
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condizione: New. 2012. Paperback. . . . . . Codice articolo V9781468467802
Quantità: 15 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 340. Codice articolo 2697856532
Quantità: 4 disponibili
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Codice articolo C9781468467802
Quantità: Più di 20 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 340 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam. Codice articolo 94540747
Quantità: 4 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. 340. Codice articolo 1897856542
Quantità: 4 disponibili
Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New. 2012. Paperback. . . . . . Books ship from the US and Ireland. Codice articolo V9781468467802
Quantità: 15 disponibili