Probabilistic Inference and Statistical Methods in Network Analysis, Olga Moreira
Автор: Wainwright Martin J Название: Cambridge Series in Statistical and Probabilistic Mathematic ISBN: 1108498027 ISBN-13(EAN): 9781108498029 Издательство: Cambridge Academ Рейтинг: Цена: 71810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Recent years have seen an explosion in the volume and variety of data collected in scientific disciplines from astronomy to genetics and industrial settings ranging from Amazon to Uber. This graduate text equips readers in statistics, machine learning, and related fields to understand, apply, and adapt modern methods suited to large-scale data.
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.
Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.
By the time you reach the end of the book (and online material) you will have gained:
A clear appreciation of the importance of a statistical approach to the design of your experiments,
A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.
The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
Автор: Box, George E. P. Tiao, George C. Название: Bayesian inference in statistical analysis ISBN: 0471574287 ISBN-13(EAN): 9780471574286 Издательство: Wiley Рейтинг: Цена: 169960.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designed to form the basis of a graduate course on Bayesian inference, this textbook discusses important general issues of the Bayesian approach. It investigates problems, illustrating the appropriate analysis of mathematical results with numerical examples.
Автор: Cooper, George R.; McGillem, Clare D. Название: Probabilistic Methods of Signal and System Analysis ISBN: 0195123549 ISBN-13(EAN): 9780195123548 Издательство: Oxford Academ Рейтинг: Цена: 242870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Originally published in 1971, this text is intended for signals and systems courses which emphasize probability. It provides an introduction to probability theory, statistics, random processes and the analysis of systems with random inputs. This edition has been updated and uses Matlab.
Автор: Chiara Brombin; Luigi Salmaso; Lara Fontanella; Lu Название: Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications ISBN: 3319263102 ISBN-13(EAN): 9783319263106 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests.
Автор: J.S. Byrnes; Kathryn A. Hargreaves; Karl Berry Название: Probabilistic and Stochastic Methods in Analysis, with Applications ISBN: 0792318048 ISBN-13(EAN): 9780792318040 Издательство: Springer Рейтинг: Цена: 437900.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Contains three expositions on wavelets, frames and their applications. This book includes the relation between probability and partial differential equations, including probabilistic representations of solutions to elliptic and parabolic PDEs.
Автор: J.S. Byrnes; Kathryn A. Hargreaves; Karl Berry Название: Probabilistic and Stochastic Methods in Analysis, with Applications ISBN: 9401052395 ISBN-13(EAN): 9789401052399 Издательство: Springer Рейтинг: Цена: 279500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Proceedings of the NATO Advanced Study Institute, Il Ciocco, Italy, July 14-27, 1991
Автор: Crane Название: Probabilistic Foundations of Statistical Network Analysis ISBN: 1138585998 ISBN-13(EAN): 9781138585997 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE. ? ? ? ? ? ?
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Agarwal Название: Statistical Methods for Recommender Systems ISBN: 1107036070 ISBN-13(EAN): 9781107036079 Издательство: Cambridge Academ Рейтинг: Цена: 50680.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.
Автор: Vershynin, Roman (university Of Michigan, Ann Arbor) Название: Cambridge series in statistical and probabilistic mathematics ISBN: 1108415199 ISBN-13(EAN): 9781108415194 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The data sciences are moving fast, and probabilistic methods are both the foundation and a driver. This highly motivated text brings beginners up to speed quickly and provides working data scientists with powerful new tools. Ideal for a basic second course in probability with a view to data science applications, it is also suitable for self-study.
Автор: Bernhard Schipp; Walter Kr?mer Название: Statistical Inference, Econometric Analysis and Matrix Algebra ISBN: 3790825778 ISBN-13(EAN): 9783790825770 Издательство: Springer Рейтинг: Цена: 172350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A collection of essays that extends the frontiers of knowledge in econometrics as well as classical fields of statistical inference. It presents advances in stochastic processes, in the design of experiments and in the analysis of variance. It provides insights into advanced approaches in quantitative methods.
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