| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
191121b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781138630154 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
003 |
| Item number |
CRA |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Crane, Harry |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Probabilistic foundations of statistical network analysis |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Boca Raton |
| Name of publisher, distributor, etc |
Chapman and Hall/CRC |
| Date of publication, distribution, etc |
2018 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xx, 236 p. |
| Other physical details |
ill. |
| Dimensions |
24 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
38.99 |
| Price type code |
GBP |
| Unit of pricing |
93.50 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Monographs on statistics and applied probability |
| Volume number/sequential designation |
v. 157 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author's incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Statistical methods |
|
|---|
| Topical term or geographic name as entry element |
Network analysis |
|
|---|
| Topical term or geographic name as entry element |
System analysis |
|
|---|
| Topical term or geographic name as entry element |
Mathematical models |
|
|---|
| Topical term or geographic name as entry element |
Probabilities |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |