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1. |
Record Nr. |
UNINA9910715700403321 |
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Titolo |
Message from the President of the United States, transmitting additional documents in relation to the dispute between the State of Maine and the British Province of New Brunswick. February 27, 1839. Referred to the Committee on Foreign Relations, and ordered to be printed, and that 5,000 additional copies be furnished for the use of the Senate |
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Pubbl/distr/stampa |
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[Washington, D.C.] : , : [publisher not identified], , 1839 |
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Descrizione fisica |
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1 online resource (8 pages) |
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Collana |
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Senate document / 25th Congress, 3rd session. Senate ; ; no. 271 |
[United States congressional serial set] ; ; [serial no. 341] |
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Altri autori (Persone) |
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Van BurenMartin <1782-1862.> |
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Soggetti |
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Aggression (International law) |
Arrest |
Boundaries |
Diplomacy |
Government liability (International law) |
Claims |
International relations |
Jurisdiction |
Lumber trade |
Military readiness |
Territories and possessions |
Timber |
Aroostook War, 1839 |
Americans - Foreign countries |
Civil service |
Legislative materials. |
Northeast boundary of the United States |
Great Britain Territories and possessions |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Batch processed record: Metadata reviewed, not verified. Some fields updated by batch processes. |
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FDLP item number not assigned. |
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2. |
Record Nr. |
UNINA9910254291403321 |
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Autore |
Lanchier Nicolas |
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Titolo |
Stochastic Modeling / / by Nicolas Lanchier |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
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ISBN |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (XIII, 303 p. 63 illus., 6 illus. in color.) |
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Collana |
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Universitext, , 0172-5939 |
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Disciplina |
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Soggetti |
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Probabilities |
Mathematical models |
Probability Theory and Stochastic Processes |
Mathematical Modeling and Industrial Mathematics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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1. Basics of Measure and Probability Theory -- 2. Distribution and Conditional Expectation -- 3. Limit Theorems -- 4. Stochastic Processes: General Definition -- 5. Martingales -- 6. Branching Processes -- 7. Discrete-time Markov Chains -- 8. Symmetric Simple Random Walks -- 9. Poisson Point and Poisson Processes -- 10. Continuous-time Markov Chains -- 11. Logistic Growth Process -- 12. Wright-Fisher and Moran Models -- 13. Percolation Models -- 14. Interacting Particle Systems -- 15. The Contact Process -- 16. The Voter Model -- 17. Numerical Simulations in C and Matlab. |
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Sommario/riassunto |
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Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review |
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of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright–Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and Matlab™. |
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