Probability for statistics and machine learning : fundamentals and advanced topics / Anirban DasGupta.

By: DasGupta, Anirban Material type: Text

TextLanguage: English Series: Springer texts in statisticsPublication details: New York : Springer, c2011. Description: xix, 782 p. : ill. ; 24 cmISBN: 1441996338; 9781441996336; 9781441996343 (ebk.)Subject(s): Probabilities | Stochastic processes | Mathematical statisticsDDC classification: 519.2 LOC classification: QA273 | .D275 2011Online resources: WorldCat details | E-book Fulltext

Contents:

TOC Review of univariate probability -- Multivariate discrete distributions -- Multidimensional densities -- Advanced distribution theory -- Multivariate normal and related distributions -- Finite sample theory of order statistics and extremes -- Essential asymptotics and applications -- Characteristics functions and applications -- Asymptotoics of extremes and order statistics -- Markov chains and application -- Random walks -- Brownian motion and Gaussian processes -- Poisson processes and applications -- Discrete time martingales and concentration inequalities -- Probability metrics -- Empirical processes and VC theory -- Large deviations -- The exponential family and statistical applications -- Simulation and Markov chain Monte Carlo -- Useful tools for statistics and machine learning.

Summary: Summary: This accessible book provides a versatile treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine Read more...

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 5 )
Comments ( 0 )

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
E-Book	EWU Library E-book	Non-fiction	519.2 DAP 2011 (Browse shelf(Opens below))		Not for loan
Text	EWU Library Reserve Section	Non-fiction	519.2 DAP 2011 (Browse shelf(Opens below))	C-1	Not For Loan		26617

Total holds: 0

Includes bibliographical references and indexes.

TOC Review of univariate probability --
Multivariate discrete distributions --
Multidimensional densities --
Advanced distribution theory --
Multivariate normal and related distributions --
Finite sample theory of order statistics and extremes --
Essential asymptotics and applications --
Characteristics functions and applications --
Asymptotoics of extremes and order statistics --
Markov chains and application --
Random walks --
Brownian motion and Gaussian processes --
Poisson processes and applications --
Discrete time martingales and concentration inequalities --
Probability metrics --
Empirical processes and VC theory --
Large deviations --
The exponential family and statistical applications --
Simulation and Markov chain Monte Carlo --
Useful tools for statistics and machine learning.

Summary:
This accessible book provides a versatile treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine Read more...

Saifun Momota

There are no comments on this title.

to post a comment.