Lectures in Probability and Statistics

Lectures in Probability and Statistics

With contributions by numerous experts

Author: Guido Del Pino

Publisher: Lecture Notes in Mathematics

ISBN: STANFORD:36105032339777

Category: Mathematics

Page: 504

View: 237

With contributions by numerous experts
Categories: Mathematics

Lectures on Probability Theory and Statistics

Lectures on Probability Theory and Statistics

This volume contains lectures given at the Saint-Flour Summer School of Probability Theory during the period 8th-24th July, 1999. We thank the authors for all the hard work they accomplished.

Author: Erwin Bolthausen

Publisher: Springer

ISBN: 9783540479444

Category: Mathematics

Page: 474

View: 517

This volume contains lectures given at the Saint-Flour Summer School of Probability Theory during the period 8th-24th July, 1999. We thank the authors for all the hard work they accomplished. Their lectures are a work of reference in their domain. The School brought together 85 participants, 31 of whom gave a lecture concerning their research work. At the end of this volume you will find the list of participants and their papers. Finally, to facilitate research concerning previous schools we give here the number of the volume of "Lecture Notes" where they can be found: Lecture Notes in Mathematics 1975: n ° 539- 1971: n ° 307- 1973: n ° 390- 1974: n ° 480- 1979: n ° 876- 1976: n ° 598- 1977: n ° 678- 1978: n ° 774- 1980: n ° 929- 1981: n ° 976- 1982: n ° 1097- 1983: n ° 1117- 1988: n ° 1427- 1984: n ° 1180- 1985-1986 et 1987: n ° 1362- 1989: n ° 1464- 1990: n ° 1527- 1991: n ° 1541- 1992: n ° 1581- 1993: n ° 1608- 1994: n ° 1648- 1995: n ° 1690- 1996: n ° 1665- 1997: n ° 1717- 1998: n ° 1738- Lecture Notes in Statistics 1971: n ° 307- Table of Contents Part I Erwin Bolthausen: Large Deviations and Interacting Random Walks 1 On the construction of the three-dimensional polymer measure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Self-attracting random walks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3 One-dimensional pinning-depinning transitions. . . . . . . . . . . 105 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Categories: Mathematics

Lectures on Probability Theory and Mathematical Statistics 3rd Edition

Lectures on Probability Theory and Mathematical Statistics   3rd Edition

The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics.

Author: Marco Taboga

Publisher: Createspace Independent Publishing Platform

ISBN: 1981369198

Category: Mathematical statistics

Page: 670

View: 399

The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. There are hundreds of examples, solved exercises and detailed derivations of important results. The step-by-step approach makes the book easy to understand and ideal for self-study. One of the main aims of the book is to be a time saver: it contains several results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books. The topics covered by the book are as follows. PART 1 - MATHEMATICAL TOOLS: set theory, permutations, combinations, partitions, sequences and limits, review of differentiation and integration rules, the Gamma and Beta functions. PART 2 - FUNDAMENTALS OF PROBABILITY: events, probability, independence, conditional probability, Bayes' rule, random variables and random vectors, expected value, variance, covariance, correlation, covariance matrix, conditional distributions and conditional expectation, independent variables, indicator functions. PART 3 - ADDITIONAL TOPICS IN PROBABILITY THEORY: probabilistic inequalities, construction of probability distributions, transformations of probability distributions, moments and cross-moments, moment generating functions, characteristic functions. PART 4 - PROBABILITY DISTRIBUTIONS: Bernoulli, binomial, Poisson, uniform, exponential, normal, Chi-square, Gamma, Student's t, F, multinomial, multivariate normal, multivariate Student's t, Wishart. PART 5 - MORE DETAILS ABOUT THE NORMAL DISTRIBUTION: linear combinations, quadratic forms, partitions. PART 6 - ASYMPTOTIC THEORY: sequences of random vectors and random variables, pointwise convergence, almost sure convergence, convergence in probability, mean-square convergence, convergence in distribution, relations between modes of convergence, Laws of Large Numbers, Central Limit Theorems, Continuous Mapping Theorem, Slutsky's Theorem. PART 7 - FUNDAMENTALS OF STATISTICS: statistical inference, point estimation, set estimation, hypothesis testing, statistical inferences about the mean, statistical inferences about the variance.
Categories: Mathematical statistics

Lectures on Probability Theory and Statistics

Lectures on Probability Theory and Statistics

Annals of Probability 17, 1303–1321, Durrett, R. T., Schonmann, R. H., and Tanaka, N. I. (1989). Correlation lengths for oriented percolation. Journal of Statistical Physics 55, 965–979. Edwards, R. G. and Sokal, A. D. (1988).

Author: Evarist Giné

Publisher: Springer

ISBN: 9783540692102

Category: Mathematics

Page: 424

View: 396

Nur Contents aufnehmen
Categories: Mathematics

Lectures on Probability Theory and Statistics

Lectures on Probability Theory and Statistics

J.L. Cardy , Scaling and renormalization in statistical physics , Cambridge Lecture Notes in Physics 5 , Cambridge University Press , 1996 . 33. J.L. Cardy ( 1998 ) , The number of incipient spanning clusters in twodimensional ...

Author: Wendelin Werner

Publisher: Springer Science & Business Media

ISBN: 3540213163

Category:

Page: 212

View: 601

Categories:

Philosophical Lectures on Probability

Philosophical Lectures on Probability

This book (based on a course held in 1979) explains in a language accessible also to non-mathematicians the fundamental tenets and implications of subjectivism, according to which the probability of any well specified fact F refers to the ...

Author: Bruno de Finetti

Publisher: Springer Science & Business Media

ISBN: 9781402082016

Category: Science

Page: 239

View: 613

Bruno de Finetti (1906–1985) is the founder of the subjective interpretation of probability, together with the British philosopher Frank Plumpton Ramsey. His related notion of “exchangeability” revolutionized the statistical methodology. This book (based on a course held in 1979) explains in a language accessible also to non-mathematicians the fundamental tenets and implications of subjectivism, according to which the probability of any well specified fact F refers to the degree of belief actually held by someone, on the ground of her whole knowledge, on the truth of the assertion that F obtains.
Categories: Science

Moment sos Hierarchy The Lectures In Probability Statistics Computational Geometry Control And Nonlinear Pdes

Moment sos Hierarchy  The  Lectures In Probability  Statistics  Computational Geometry  Control And Nonlinear Pdes

SOS approximations of nonnegative polynomials via simple high degree perturbations, Math. Z. 256, pp. 99– 112. Lasserre, J. B. and Putinar, M. (2015). Algebraic-exponential data recovery from moments, Discrete & Comput. Geometry 54, pp.

Author: Didier Henrion

Publisher: World Scientific

ISBN: 9781786348555

Category: Mathematics

Page: 248

View: 408

The Moment-SOS hierarchy is a powerful methodology that is used to solve the Generalized Moment Problem (GMP) where the list of applications in various areas of Science and Engineering is almost endless. Initially designed for solving polynomial optimization problems (the simplest example of the GMP), it applies to solving any instance of the GMP whose description only involves semi-algebraic functions and sets. It consists of solving a sequence (a hierarchy) of convex relaxations of the initial problem, and each convex relaxation is a semidefinite program whose size increases in the hierarchy.The goal of this book is to describe in a unified and detailed manner how this methodology applies to solving various problems in different areas ranging from Optimization, Probability, Statistics, Signal Processing, Computational Geometry, Control, Optimal Control and Analysis of a certain class of nonlinear PDEs. For each application, this unconventional methodology differs from traditional approaches and provides an unusual viewpoint. Each chapter is devoted to a particular application, where the methodology is thoroughly described and illustrated on some appropriate examples.The exposition is kept at an appropriate level of detail to aid the different levels of readers not necessarily familiar with these tools, to better know and understand this methodology.
Categories: Mathematics

Ecole D ete de Probabilites de Saint Flour

Ecole D ete de Probabilites de Saint Flour

Lecture Notes in Mathematics This series reports on new developments in mathematical research and teaching - quickly, informally and at a high level. The type of material considered for publication includes 1. Research monographs 2.

Author: J. Bertoin

Publisher: Springer Science & Business Media

ISBN: 3540665935

Category: Mathematics

Page: 308

View: 770

Lecture Notes in Mathematics This series reports on new developments in mathematical research and teaching - quickly, informally and at a high level. The type of material considered for publication includes 1. Research monographs 2. Lectures on a new field or presentations of a new angle in a classical field 3. Summer schools and intensive courses on topics of current research Texts which are out of print but still in demand may also be considered. The timeliness of a manuscript is sometimes more important than its form, which might be preliminary or tentative. Details of the editorial policy can be found on the inside front-cover of a current volume. Manuscripts should be submitted in camera-ready form according to Springer-Verlag's specification: technical instructions will be sent on request. TEX macros may be found at: http://www.springer.de/math/authors/b-tex.html Select the version of TEX you use and then click on "Monographs". A subject index should be included. We recommend contacting the publisher or the series editors at an early stage of your project. Addresses are given on the inside back-cover.
Categories: Mathematics

Mathematical Theory of Probability and Statistics

Mathematical Theory of Probability and Statistics

PREFACE Richard von Mises' scientific work comprises two major fields: mechanics and probability-statistics; ... The results of his thinking were incorporated in Lectures on Probability and Statistics he gave repeatedly at Harvard ...

Author: Richard von Mises

Publisher: Academic Press

ISBN: 9781483264028

Category: Mathematics

Page: 708

View: 395

Mathematical Theory of Probability and Statistics focuses on the contributions and influence of Richard von Mises on the processes, methodologies, and approaches involved in the mathematical theory of probability and statistics. The publication first elaborates on fundamentals, general label space, and basic properties of distributions. Discussions focus on Gaussian distribution, Poisson distribution, mean value variance and other moments, non-countable label space, basic assumptions, operations, and distribution function. The text then ponders on examples of combined operations and summation of chance variables characteristic function. The book takes a look at the asymptotic distribution of the sum of chance variables and probability inference. Topics include inference from a finite number of observations, law of large numbers, asymptotic distributions, limit distribution of the sum of independent discrete random variables, probability of the sum of rare events, and probability density. The text also focuses on the introduction to the theory of statistical functions and multivariate statistics. The publication is a dependable source of information for researchers interested in the mathematical theory of probability and statistics
Categories: Mathematics

Lectures on Probability Theory and Mathematical Statistics 2nd Edition

Lectures on Probability Theory and Mathematical Statistics   2nd Edition

This book is a collection of lectures on probability theory and mathematical statistics.

Author: Marco Taboga

Publisher:

ISBN: 1480215236

Category: Mathematical statistics

Page: 656

View: 617

This book is a collection of lectures on probability theory and mathematical statistics. It provides an accessible introduction to topics that are not usually found in elementary textbooks. It collects results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books.The main topics covered by the book are as follows.PART 1 - MATHEMATICAL TOOLS: set theory, permutations, combinations, partitions, sequences and limits, review of differentiation and integration rules, the Gamma and Beta functions.PART 2 - FUNDAMENTALS OF PROBABILITY: events, probability, independence, conditional probability, Bayes' rule, random variables and random vectors, expected value, variance, covariance, correlation, covariance matrix, conditional distributions and conditional expectation, independent variables, indicator functions.PART 3 - ADDITIONAL TOPICS IN PROBABILITY THEORY: probabilistic inequalities, construction of probability distributions, transformations of probability distributions, moments and cross-moments, moment generating functions, characteristic functions.PART 4 - PROBABILITY DISTRIBUTIONS: Bernoulli, binomial, Poisson, uniform, exponential, normal, Chi-square, Gamma, Student's t, F, multinomial, multivariate normal, multivariate Student's t, Wishart.PART 5 - MORE DETAILS ABOUT THE NORMAL DISTRIBUTION: linear combinations, quadratic forms, partitions.PART 6 - ASYMPTOTIC THEORY: sequences of random vectors and random variables, pointwise convergence, almost sure convergence, convergence in probability, mean-square convergence, convergence in distribution, relations between modes of convergence, Laws of Large Numbers, Central Limit Theorems, Continuous Mapping Theorem, Slutski's Theorem.PART 7 - FUNDAMENTALS OF STATISTICS: statistical inference, point estimation, set estimation, hypothesis testing, statistical inferences about the mean, statistical inferences about the variance.
Categories: Mathematical statistics