The Resource Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta
Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta
Resource Information
The item Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 1 library branch.
 Language
 eng
 Extent
 xix, 782 pages
 Contents

 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
 Isbn
 9781441996336
 Label
 Probability for statistics and machine learning : fundamentals and advanced topics
 Title
 Probability for statistics and machine learning
 Title remainder
 fundamentals and advanced topics
 Statement of responsibility
 Anirban DasGupta
 Language
 eng
 Cataloging source
 YDXCP
 http://library.link/vocab/creatorName
 DasGupta, Anirban
 Illustrations
 illustrations
 Index
 index present
 LC call number
 QA274
 LC item number
 .D28 2011
 Literary form
 non fiction
 Nature of contents
 bibliography
 Series statement
 Springer texts in statistics
 http://library.link/vocab/subjectName

 Probabilities
 Stochastic processes
 Mathematical statistics
 Machine learning
 Target audience
 adult
 Label
 Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta
 Bibliography note
 Includes bibliographical references and indexes
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 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
 Control code
 706920643
 Dimensions
 24 cm
 Extent
 xix, 782 pages
 Isbn
 9781441996336
 Lccn
 2011924777
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
 System control number
 (OCoLC)706920643
 Label
 Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta
 Bibliography note
 Includes bibliographical references and indexes
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 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
 Control code
 706920643
 Dimensions
 24 cm
 Extent
 xix, 782 pages
 Isbn
 9781441996336
 Lccn
 2011924777
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
 System control number
 (OCoLC)706920643
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.missouri.edu/portal/Probabilityforstatisticsandmachinelearning/GBY1mcLDeOE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/Probabilityforstatisticsandmachinelearning/GBY1mcLDeOE/">Probability for statistics and machine learning : fundamentals and advanced topics, Anirban DasGupta</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>