Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 656
Book Description
This journal, covering topics in mathematical statistics, split into Annals of probability and Annals of statistics in 1973.
The Annals of Mathematical Statistics
Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 656
Book Description
This journal, covering topics in mathematical statistics, split into Annals of probability and Annals of statistics in 1973.
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 656
Book Description
This journal, covering topics in mathematical statistics, split into Annals of probability and Annals of statistics in 1973.
Guide to Tables in Mathematical Statistics
Author: Joseph Arthur Greenwood
Publisher: Princeton University Press
ISBN: 1400886813
Category : Mathematics
Languages : en
Pages : 1081
Book Description
This book is exclusively devoted to the tables of mathematical statistics. It catalogues a large selection of tables in the field of mathematical statistics, with a small selection of mathematical tables lying outside statistics but often used with statistical tables. Originally published in 1962. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Publisher: Princeton University Press
ISBN: 1400886813
Category : Mathematics
Languages : en
Pages : 1081
Book Description
This book is exclusively devoted to the tables of mathematical statistics. It catalogues a large selection of tables in the field of mathematical statistics, with a small selection of mathematical tables lying outside statistics but often used with statistical tables. Originally published in 1962. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
All of Statistics
Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446
Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446
Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Statistics for Mathematicians
Author: Victor M. Panaretos
Publisher: Birkhäuser
ISBN: 3319283413
Category : Mathematics
Languages : en
Pages : 190
Book Description
This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
Publisher: Birkhäuser
ISBN: 3319283413
Category : Mathematics
Languages : en
Pages : 190
Book Description
This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
Statistics for High-Dimensional Data
Author: Peter Bühlmann
Publisher: Springer Science & Business Media
ISBN: 364220192X
Category : Mathematics
Languages : en
Pages : 568
Book Description
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
Publisher: Springer Science & Business Media
ISBN: 364220192X
Category : Mathematics
Languages : en
Pages : 568
Book Description
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
Stochastic Networks
Author: Paul Glasserman
Publisher: Springer Science & Business Media
ISBN: 146124062X
Category : Mathematics
Languages : en
Pages : 305
Book Description
Two of the most exciting topics of current research in stochastic networks are the complementary subjects of stability and rare events - roughly, the former deals with the typical behavior of networks, and the latter with significant atypical behavior. Both are classical topics, of interest since the early days of queueing theory, that have experienced renewed interest mo tivated by new applications to emerging technologies. For example, new stability issues arise in the scheduling of multiple job classes in semiconduc tor manufacturing, the so-called "re-entrant lines;" and a prominent need for studying rare events is associated with the design of telecommunication systems using the new ATM (asynchronous transfer mode) technology so as to guarantee quality of service. The objective of this volume is hence to present a sample - by no means comprehensive - of recent research problems, methodologies, and results in these two exciting and burgeoning areas. The volume is organized in two parts, with the first part focusing on stability, and the second part on rare events. But it is impossible to draw sharp boundaries in a healthy field, and inevitably some articles touch on both issues and several develop links with other areas as well. Part I is concerned with the issue of stability in queueing networks.
Publisher: Springer Science & Business Media
ISBN: 146124062X
Category : Mathematics
Languages : en
Pages : 305
Book Description
Two of the most exciting topics of current research in stochastic networks are the complementary subjects of stability and rare events - roughly, the former deals with the typical behavior of networks, and the latter with significant atypical behavior. Both are classical topics, of interest since the early days of queueing theory, that have experienced renewed interest mo tivated by new applications to emerging technologies. For example, new stability issues arise in the scheduling of multiple job classes in semiconduc tor manufacturing, the so-called "re-entrant lines;" and a prominent need for studying rare events is associated with the design of telecommunication systems using the new ATM (asynchronous transfer mode) technology so as to guarantee quality of service. The objective of this volume is hence to present a sample - by no means comprehensive - of recent research problems, methodologies, and results in these two exciting and burgeoning areas. The volume is organized in two parts, with the first part focusing on stability, and the second part on rare events. But it is impossible to draw sharp boundaries in a healthy field, and inevitably some articles touch on both issues and several develop links with other areas as well. Part I is concerned with the issue of stability in queueing networks.
Fundamentals of Statistical Exponential Families
Author: Lawrence D. Brown
Publisher: IMS
ISBN: 9780940600102
Category : Business & Economics
Languages : en
Pages : 302
Book Description
Publisher: IMS
ISBN: 9780940600102
Category : Business & Economics
Languages : en
Pages : 302
Book Description
The King's English
Author: Henry Watson Fowler
Publisher:
ISBN:
Category : English language
Languages : en
Pages : 172
Book Description
Publisher:
ISBN:
Category : English language
Languages : en
Pages : 172
Book Description
An Invitation to Statistics in Wasserstein Space
Author: Victor M. Panaretos
Publisher: Springer Nature
ISBN: 3030384381
Category : Mathematics
Languages : en
Pages : 157
Book Description
This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation. Further to reviewing state-of-the-art aspects, it also provides an accessible introduction to the fundamentals of this current topic, as well as an overview that will serve as an invitation and catalyst for further research. Statistics in Wasserstein spaces represents an emerging topic in mathematical statistics, situated at the interface between functional data analysis (where the data are functions, thus lying in infinite dimensional Hilbert space) and non-Euclidean statistics (where the data satisfy nonlinear constraints, thus lying on non-Euclidean manifolds). The Wasserstein space provides the natural mathematical formalism to describe data collections that are best modeled as random measures on Euclidean space (e.g. images and point processes). Such random measures carry the infinite dimensional traits of functional data, but are intrinsically nonlinear due to positivity and integrability restrictions. Indeed, their dominating statistical variation arises through random deformations of an underlying template, a theme that is pursued in depth in this monograph.
Publisher: Springer Nature
ISBN: 3030384381
Category : Mathematics
Languages : en
Pages : 157
Book Description
This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation. Further to reviewing state-of-the-art aspects, it also provides an accessible introduction to the fundamentals of this current topic, as well as an overview that will serve as an invitation and catalyst for further research. Statistics in Wasserstein spaces represents an emerging topic in mathematical statistics, situated at the interface between functional data analysis (where the data are functions, thus lying in infinite dimensional Hilbert space) and non-Euclidean statistics (where the data satisfy nonlinear constraints, thus lying on non-Euclidean manifolds). The Wasserstein space provides the natural mathematical formalism to describe data collections that are best modeled as random measures on Euclidean space (e.g. images and point processes). Such random measures carry the infinite dimensional traits of functional data, but are intrinsically nonlinear due to positivity and integrability restrictions. Indeed, their dominating statistical variation arises through random deformations of an underlying template, a theme that is pursued in depth in this monograph.
Tables for Computing Bivariate Normal Probabilities
Author: Donald Bruce Owen
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 22
Book Description
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 22
Book Description