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Probability Statistics And Stochastic Processes

Author: Peter Olofsson
Publisher: John Wiley & Sons
ISBN: 0470889748
Size: 11.96 MB
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"This book provides a unique and balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and renewal theory. Many new introductory problems and exercises have also been added. This book combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The book begins with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions. The next two chapters introduce limit theorems and simulation. Also included is a chapter on statistical inference with a focus on Bayesian statistics, which is an important, though often neglected, topic for undergraduate-level texts. Markov chains in discrete and continuous time are also discussed within the book. More than 400 examples are interspersed throughout to help illustrate concepts and theory and to assist readers in developing an intuitive sense of the subject. Readers will find many of the examples to be both entertaining and thought provoking. This is also true for the carefully selected problems that appear at the end of each chapter"--

Probability Statistics And Stochastic Processes

Author: Peter Olofsson
Publisher: John Wiley & Sons
ISBN: 1118231309
Size: 55.25 MB
Format: PDF
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Praise for the First Edition ". . . an excellent textbook . . . well organized and neatlywritten." —Mathematical Reviews ". . . amazingly interesting . . ." —Technometrics Thoroughly updated to showcase the interrelationships betweenprobability, statistics, and stochastic processes, Probability,Statistics, and Stochastic Processes, Second Edition preparesreaders to collect, analyze, and characterize data in their chosenfields. Beginning with three chapters that develop probability theoryand introduce the axioms of probability, random variables, andjoint distributions, the book goes on to present limit theorems andsimulation. The authors combine a rigorous, calculus-baseddevelopment of theory with an intuitive approach that appeals toreaders' sense of reason and logic. Including more than 400examples that help illustrate concepts and theory, the SecondEdition features new material on statistical inference and a wealthof newly added topics, including: Consistency of point estimators Large sample theory Bootstrap simulation Multiple hypothesis testing Fisher's exact test and Kolmogorov-Smirnov test Martingales, renewal processes, and Brownian motion One-way analysis of variance and the general linear model Extensively class-tested to ensure an accessible presentation,Probability, Statistics, and Stochastic Processes, SecondEdition is an excellent book for courses on probability andstatistics at the upper-undergraduate level. The book is also anideal resource for scientists and engineers in the fields ofstatistics, mathematics, industrial management, andengineering.

Nonparametric Statistics For Stochastic Processes

Author: D. Bosq
Publisher: Springer Science & Business Media
ISBN: 1461217180
Size: 16.22 MB
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This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rates of convergence which appear in continuous time are presented in Chapters 4 and 5. This second edition is extensively revised and it contains two new chapters. Chapter 6 discusses the surprising local time density estimator. Chapter 7 gives a detailed account of implementation of nonparametric method and practical examples in economics, finance and physics. Comarison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting. The prerequisite is a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the Unviersity of Paris 6 (Pierre et Marie Curie). He is Editor-in-Chief of "Statistical Inference for Stochastic Processes" and an editor of "Journal of Nonparametric Statistics". He is an elected member of the International Statistical Institute. He has published about 90 papers or works in nonparametric statistics and four books.

Mathematical Statistics And Stochastic Processes

Author: Denis Bosq
Publisher: John Wiley & Sons
ISBN: 1118586271
Size: 18.77 MB
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Generally, books on mathematical statistics are restricted tothe case of independent identically distributed random variables.In this book however, both this case AND the case of dependentvariables, i.e. statistics for discrete and continuous timeprocesses, are studied. This second case is very important fortoday’s practitioners. Mathematical Statistics and Stochastic Processes is based ondecision theory and asymptotic statistics and contains up-to-dateinformation on the relevant topics of theory of probability,estimation, confidence intervals, non-parametric statistics androbustness, second-order processes in discrete and continuous timeand diffusion processes, statistics for discrete and continuoustime processes, statistical prediction, and complements inprobability. This book is aimed at students studying courses on probability withan emphasis on measure theory and for all practitioners who applyand use statistics and probability on a daily basis.

Statistical Inference In Stochastic Processes

Author: N.U. Prabhu
Publisher: CRC Press
ISBN: 9780824784171
Size: 66.68 MB
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Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di

Introduction To Probability Statistics And Random Processes

Author: Hossein Pishro-Nik
Publisher:
ISBN: 9780990637202
Size: 80.89 MB
Format: PDF, ePub
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The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.

Probability And Statistics Volume I

Author: Reinhard Viertl
Publisher: EOLSS Publications
ISBN: 1848260520
Size: 30.70 MB
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Probability and Statistics theme is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The Theme with contributions from distinguished experts in the field, discusses Probability and Statistics. Probability is a standard mathematical concept to describe stochastic uncertainty. Probability and Statistics can be considered as the two sides of a coin. They consist of methods for modeling uncertainty and measuring real phenomena. Today many important political, health, and economic decisions are based on statistics. This theme is structured in five main topics: Probability and Statistics; Probability Theory; Stochastic Processes and Random Fields; Probabilistic Models and Methods; Foundations of Statistics, which are then expanded into multiple subtopics, each as a chapter. These three volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs

Stochastic Processes

Author: Sheldon M. Ross
Publisher: John Wiley & Sons Inc
ISBN:
Size: 29.61 MB
Format: PDF, Mobi
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A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.

Introduction To Probability And Stochastic Processes With Applications

Author: Liliana Blanco Castañeda
Publisher: John Wiley & Sons
ISBN: 1118344960
Size: 24.93 MB
Format: PDF
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An easily accessible, real-world approach to probability andstochastic processes Introduction to Probability and Stochastic Processes withApplications presents a clear, easy-to-understand treatment ofprobability and stochastic processes, providing readers with asolid foundation they can build upon throughout their careers. Withan emphasis on applications in engineering, applied sciences,business and finance, statistics, mathematics, and operationsresearch, the book features numerous real-world examples thatillustrate how random phenomena occur in nature and how to useprobabilistic techniques to accurately model these phenomena. The authors discuss a broad range of topics, from the basicconcepts of probability to advanced topics for further study,including Itô integrals, martingales, and sigma algebras.Additional topical coverage includes: Distributions of discrete and continuous random variablesfrequently used in applications Random vectors, conditional probability, expectation, andmultivariate normal distributions The laws of large numbers, limit theorems, and convergence ofsequences of random variables Stochastic processes and related applications, particularly inqueueing systems Financial mathematics, including pricing methods such asrisk-neutral valuation and the Black-Scholes formula Extensive appendices containing a review of the requisitemathematics and tables of standard distributions for use inapplications are provided, and plentiful exercises, problems, andsolutions are found throughout. Also, a related website featuresadditional exercises with solutions and supplementary material forclassroom use. Introduction to Probability and StochasticProcesses with Applications is an ideal book for probabilitycourses at the upper-undergraduate level. The book is also avaluable reference for researchers and practitioners in the fieldsof engineering, operations research, and computer science whoconduct data analysis to make decisions in their everyday work.