Probability, random processes, and statistical analysis
Hisashi Kobayashi
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at 250 WPM12h 30m
The average reader, reading at a speed of 250 WPM, would take 12h 30m to read Probability, random processes, and statistical analysis.
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Probability, random processes, and statistical analysis
Published
2012
Publisher
Cambridge University Press
Pages
750
ISBN-13
9781283382465
Description
"Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and It's process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum-Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals"-- "Probability, Random Processes, and Statistical Analysis Together with the fundamentals of probability, random processes, and statistical analysis, this insightful book also presents a broad range of advanced topics and applications not covered in other textbooks. Advanced topics include: - Bayesian inference and conjugate priors - Chernoff bound and large deviation approximation - Principal component analysis and singular value decomposition - Autoregressive moving average (ARMA) time series - Maximum likelihood estimation and the EM algorithm - Brownian motion, geometric Brownian motion, and Ito process - Black-Scholes differential equation for option pricing"--
Control and Dynamic Systems
Doing Data Science
Problems and Solutions in Mathematical Finance
Financial Econometrics
Introduction to probability models
Lévy processes and stochastic calculus
Frequently Asked Questions
How many pages are in Probability, random processes, and statistical analysis?
This edition of Probability, random processes, and statistical analysis has approximately 750 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Probability, random processes, and statistical analysis?
For most readers, Probability, random processes, and statistical analysis typically takes between 15h 38m and 10h 25m to complete. This is based on the book's length of approximately 187,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 12h 30m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 25 days • Estimated word count: 187,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Probability, random processes, and statistical analysis?
The estimated word count for Probability, random processes, and statistical analysis is approximately 187,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Probability, random processes, and statistical analysis?
Probability, random processes, and statistical analysis was written by Hisashi Kobayashi.
When was Probability, random processes, and statistical analysis published?
The publication date for this specific edition is 2012. The original work may have been published on a different date.