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|a QA274.2 .K63 2012
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|a 519.2
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|a UAMI
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|a Kobayashi, Hisashi.
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|a Probability, Random Processes, and Statistical Analysis :
|b Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance.
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|a Cambridge :
|b Cambridge University Press,
|c 2011.
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|a 1 online resource (814 pages)
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a Cover; Probability, Random Processes, and Statistical Analysis; Title; Copyright; Contents; Abbreviations and Acronyms; Preface; Organization of the book; Suggested course plans; Supplementary materials; Solution manuals; Lecture slides; Matlab exercises and programs; Acknowledgments; 1 Introduction; 1.1 Why study probability, random processes, and statistical analysis?; 1.1.1 Communications, information, and control systems; 1.1.2 Signal processing; 1.1.3 Machine learning; 1.1.4 Biostatistics, bioinformatics, and related fields; 1.1.5 Econometrics and mathematical finance.
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|a 1.1.6 Queueing and loss systems1.1.7 Other application domains; 1.2 History and overview; 1.2.1 Classical probability theory; 1.2.2 Modern probability theory; 1.2.3 Random processes; 1.2.3.1 Poisson process to Markov process; 1.2.3.2 Brownian motion to Itô process; 1.2.4 Statistical analysis and inference; 1.2.4.1 Frequentist statistics versus Bayesian statistics; 1.3 Discussion and further reading; Part I Probability, random variables, and statistics; 2 Probability; 2.1 Randomness in the real world; 2.1.1 Repeated experiments and statistical regularity.
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|a 2.1.2 Random experiments and relative frequencies2.2 Axioms of probability; 2.2.1 Sample space; 2.2.2 Event; 2.2.3 Probability measure; 2.2.4 Properties of probability measure; 2.3 Bernoulli trials and Bernoulli's theorem; 2.4 Conditional probability, Bayes' theorem, and statistical independence; 2.4.1 Joint probability and conditional probability; 2.4.2 Bayes' theorem; 2.4.2.1 Frequentist probabilities and Bayesian probabilities; 2.4.3 Statistical independence of events; 2.5 Summary of Chapter 2; 2.6 Discussion and further reading; 2.7 Problems; 3 Discrete random variables.
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|a 3.1 Random variables3.1.1 Distribution function; 3.1.2 Two random variables and joint distribution function; 3.2 Discrete random variables and probability distributions; 3.2.1 Joint and conditional probability distributions; 3.2.2 Moments, central moments, and variance; 3.2.3 Covariance and correlation coefficient; 3.3 Important probability distributions; 3.3.1 Bernoulli distribution and binomial distribution; 3.3.2 Geometric distribution; 3.3.3 Poisson distribution; 3.3.4 Negative binomial (or Pascal) distribution; 3.3.4.1 Shifted negative binomial distribution.
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|a 3.3.5 Zipf's law and zeta distribution3.3.5.1 Euler and Riemann zeta functions; 3.4 Summary of Chapter 3; 3.5 Discussion and further reading; 3.6 Problems; 4 Continuous random variables; 4.1 Continuous random variables; 4.1.1 Distribution function and probability density function; 4.1.2 Expectation, moments, central moments, and variance; 4.2 Important continuous random variables and their distributions; 4.2.1 Uniform distribution; 4.2.2 Exponential distribution; 4.2.3 Gamma distribution; 4.2.4 Normal (or Gaussian) distribution; 4.2.4.1 Moments of the unit normal distribution.
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|a 4.2.4.2 The normal approximation to the binomial distribution and the DeMoivre-Laplace limit theorem4.
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|a Covers the fundamental topics together with advanced theories, including the EM algorithm, hidden Markov models, and queueing and loss systems.
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|a Print version record.
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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|a Stochastic analysis.
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650 |
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|a Analyse stochastique.
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650 |
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|a Stochastic analysis
|2 fast
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700 |
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|a Mark, Brian L.
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700 |
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|a Turin, William.
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758 |
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|i has work:
|a Probability, random processes, and statistical analysis (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFXtJTkVg73mwRPGd9vDVP
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
0 |
8 |
|i Print version:
|a Kobayashi, Hisashi.
|t Probability, Random Processes, and Statistical Analysis : Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance.
|d Cambridge : Cambridge University Press, ©2011
|z 9780521895446
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856 |
4 |
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|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=807304
|z Texto completo
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938 |
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|a EBL - Ebook Library
|b EBLB
|n EBL807304
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994 |
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|a 92
|b IZTAP
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