Mathematical Foundations Of Infinite Dimensional Statistical Models
DOWNLOAD
Download Mathematical Foundations Of Infinite Dimensional Statistical Models PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Mathematical Foundations Of Infinite Dimensional Statistical Models book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Mathematical Foundations Of Infinite Dimensional Statistical Models
DOWNLOAD
Author : Evarist Giné
language : en
Publisher: Cambridge University Press
Release Date : 2016
Mathematical Foundations Of Infinite Dimensional Statistical Models written by Evarist Giné and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Business & Economics categories.
This book develops the theory of statistical inference in statistical models with an infinite-dimensional parameter space, including mathematical foundations and key decision-theoretic principles.
Analysis Of Multivariate And High Dimensional Data
DOWNLOAD
Author : Inge Koch
language : en
Publisher: Cambridge University Press
Release Date : 2014
Analysis Of Multivariate And High Dimensional Data written by Inge Koch and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Business & Economics categories.
This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.
Probability With Martingales
DOWNLOAD
Author : David Williams
language : en
Publisher: Cambridge University Press
Release Date : 1991-02-14
Probability With Martingales written by David Williams and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-02-14 with Mathematics categories.
This is a masterly introduction to the modern, and rigorous, theory of probability. The author emphasises martingales and develops all the necessary measure theory.
High Dimensional Statistics
DOWNLOAD
Author : Martin J. Wainwright
language : en
Publisher: Cambridge University Press
Release Date : 2019-02-21
High Dimensional Statistics written by Martin J. Wainwright and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Business & Economics categories.
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Foundations Of Data Science
DOWNLOAD
Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Statistical Hypothesis Testing In Context
DOWNLOAD
Author : Michael P. Fay
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Statistical Hypothesis Testing In Context written by Michael P. Fay and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Mathematics categories.
This coherent guide equips applied statisticians to make good choices and proper interpretations in real investigations facing real data.
High Dimensional Probability
DOWNLOAD
Author : Roman Vershynin
language : en
Publisher: Cambridge University Press
Release Date : 2018-09-27
High Dimensional Probability written by Roman Vershynin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Business & Economics categories.
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Model Based Clustering And Classification For Data Science
DOWNLOAD
Author : Charles Bouveyron
language : en
Publisher: Cambridge University Press
Release Date : 2019-07-25
Model Based Clustering And Classification For Data Science written by Charles Bouveyron and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Business & Economics categories.
Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.
The Fundamentals Of Heavy Tails
DOWNLOAD
Author : Jayakrishnan Nair
language : en
Publisher: Cambridge University Press
Release Date : 2022-06-09
The Fundamentals Of Heavy Tails written by Jayakrishnan Nair and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-09 with Business & Economics categories.
An accessible yet rigorous package of probabilistic and statistical tools for anyone who must understand or model extreme events.
Random Graphs And Complex Networks Volume 2
DOWNLOAD
Author : Remco van der Hofstad
language : en
Publisher: Cambridge University Press
Release Date : 2024-02-08
Random Graphs And Complex Networks Volume 2 written by Remco van der Hofstad and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-08 with Mathematics categories.
Complex networks are key to describing the connected nature of the society that we live in. This book, the second of two volumes, describes the local structure of random graph models for real-world networks and determines when these models have a giant component and when they are small-, and ultra-small, worlds. This is the first book to cover the theory and implications of local convergence, a crucial technique in the analysis of sparse random graphs. Suitable as a resource for researchers and PhD-level courses, it uses examples of real-world networks, such as the Internet and citation networks, as motivation for the models that are discussed, and includes exercises at the end of each chapter to develop intuition. The book closes with an extensive discussion of related models and problems that demonstratemodern approaches to network theory, such as community structure and directed models.