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SPIRES-BOOKS: FIND KEYWORD DISTRIBUTION PROBABILITY THEORY *END*INIT* use /tmp/qspiwww.webspi1/24028.19 QRY 131.225.70.96 . find keyword "distribution probability theory" ( in books using www

 Call number: 9783319500386:ONLINE Show nearby items on shelf Title: Stochastic Modeling Author(s): Nicolas Lanchier Date: 2017 Size: 1 online resource (XIII, 303 p. 63 illus., 6 illus. in color p.) Contents: 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 ISBN: 9783319500386 Series: eBooks Series: Springer eBooks Series: Springer 2017 package Keywords: Mathematics , Mathematical models , Probabilities , Mathematics , Probability Theory and Stochastic Processes , Mathematical Modeling and Industrial Mathematics Availability: Click here to see Library holdings or inquire at Circ Desk (x3401) Click to reserve this book Be sure to include your ID please. More info: Amazon.com More info: Barnes and Noble Full Text: Click here Location: ONLINE

 Call number: SPRINGER-2014-9783319049724:ONLINE Show nearby items on shelf Title: Statistical Theory and Inference [electronic resource] Author(s): David J Olive Date: 2014 Publisher: Cham : Springer International Publishing : Imprint: Springer Size: 1 online resource Note: This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum varianceestimators and the Cram er-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much moreaccessible to students by using the theory of exp onential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 brand namedistributions are used to illustrate the theory with many examples of exponentia l families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages ofsolutions Contents: Probability and Expectations Multivariate Distributions Exponential Families Sufficient Statistics Point Estimation I Point Estimation II Testing Statistical Hypotheses Large Sample Theory Confidence Intervals Some Useful Distributions Bayesian Methods Stuff for Students ISBN: 9783319049724 Series: eBooks Series: SpringerLink Series: Mathematics and Statistics (Springer-11649) Keywords: Statistics , Distribution (Probability theory) , Mathematical statistics Availability: Click here to see Library holdings or inquire at Circ Desk (x3401) Click to reserve this book Be sure to include your ID please. More info: Amazon.com More info: Barnes and Noble Full Text: Click here Location: ONLINE