An Introduction to Probabilistic Modeling (Undergraduate Texts in Mathematics) - gebunden oder broschiert

EAN (ISBN-13): 9780387964607
ISBN (ISBN-10): 0387964606
Gebundene Ausgabe
Erscheinungsjahr: 2007
Herausgeber: Springer-Verlag GmbH
228 Seiten
Gewicht: 0,508 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-10-12T18:28:59+02:00 (Berlin)
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ISBN/EAN: 9780387964607

ISBN - alternative Schreibweisen:
0-387-96460-6, 978-0-387-96460-7
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: bremaud
Titel des Buches: probabilistic, undergraduate text

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Daten vom Verlag:

Autor/in: Pierre Bremaud
Titel: Undergraduate Texts in Mathematics; An Introduction to Probabilistic Modeling
Verlag: Springer; Springer US
208 Seiten
Erscheinungsjahr: 1988-08-01
New York; NY; US
Sprache: Englisch
71,64 € (DE)
73,65 € (AT)
96,69 CHF (CH)
Available
XVI, 208 p.

BB; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Branching process; Conditional probability; Markov chain; Poisson process; Probability space; Probability theory; Random variable; Stochastic processes; Variance; coding; stochastic process; Probability Theory; Stochastik; BC

1 Basic Concepts and Elementary Models.- 1. The Vocabulary of Probability Theory.- 2. Events and Probability.- 3. Random Variables and Their Distributions.- 4. Conditional Probability and Independence.- 5. Solving Elementary Problems.- 6. Counting and Probability.- 7. Concrete Probability Spaces.- Illustration 1. A Simple Model in Genetics: Mendel’s Law and Hardy—Weinberg’s Theorem.- Illustration 2. The Art of Counting: The Ballot Problem and the Reflection Principle.- Illustration 3. Bertrand’s Paradox.- 2 Discrete Probability.- 1. Discrete Random Elements.- 2. Variance and Chebyshev’s Inequality.- 3. Generating Functions.- Illustration 4. An Introduction to Population Theory: Galton—Watson’s Branching Process.- Illustration 5. Shannon’s Source Coding Theorem: An Introduction to Information Theory.- 3 Probability Densities.- I. Expectation of Random Variables with a Density.- 2. Expectation of Functionals of Random Vectors.- 3. Independence.- 4. Random Variables That Are Not Discrete and Do Not Have a pd.- Illustration 6. Buffon’s Needle: A Problem in Random Geometry.- 4 Gauss and Poisson.- 1. Smooth Change of Variables.- 2. Gaussian Vectors.- 3. Poisson Processes.- 4. Gaussian Stochastic Processes.- Illustration 7. An Introduction to Bayesian Decision Theory: Tests of Gaussian Hypotheses.- 5 Convergences.- 1. Almost-Sure Convergence.- 2. Convergence in Law.- 3. The Hierarchy of Convergences.- Illustration 8. A Statistical Procedure: The Chi-Square Test.- Illustration 9. Introduction to Signal Theory: Filtering.- Additional Exercises.- Solutions to Additional Exercises.