Reflections on the Foundations of Probability and Statistics, Augustin
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10061.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Senn, Stephen Название: Dicing with death ISBN: 1108999867 ISBN-13(EAN): 9781108999861 Издательство: Cambridge Academ Рейтинг: Цена: 3325.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From measles to malaria, from clinical trials to COVID and from life tables to the law, the second edition of Dicing with Death explains how the vital decisions we have to make both individually and collectively can be informed and improved by good data, statistical reasoning and analysis.
Автор: Bradley Efron , Trevor Hastie Название: Computer Age Statistical Inference, Student Edition ISBN: 1108823416 ISBN-13(EAN): 9781108823418 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.
Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Brunton, Steven L. (university Of Washington) Kutz Название: Data-driven science and engineering ISBN: 1009098489 ISBN-13(EAN): 9781009098489 Издательство: Cambridge Academ Рейтинг: Цена: 7918.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.
Автор: Crane Название: Probabilistic Foundations of Statistical Network Analysis ISBN: 1138585998 ISBN-13(EAN): 9781138585997 Издательство: Taylor&Francis Рейтинг: Цена: 21437.00 р. 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: Bollman Название: Mathematics of Keno and Lotteries ISBN: 1138723800 ISBN-13(EAN): 9781138723801 Издательство: Taylor&Francis Рейтинг: Цена: 25265.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mathematics of Keno and Lotteries is an elementary treatment of the mathematics, primarily probability and simple combinatorics, involved in lotteries and keno. Keno has a long history as a high-advantage, high-payoff casino game, and state lottery games such as Powerball are mathematically similar.
Автор: Alan Agresti Название: Foundations of Linear and Generalized Linear Models ISBN: 1118730038 ISBN-13(EAN): 9781118730034 Издательство: Wiley Рейтинг: Цена: 16782.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models.
Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems.
Автор: Salsburg Название: Errors, Blunders And Lies ISBN: 1498795781 ISBN-13(EAN): 9781498795784 Издательство: Taylor&Francis Рейтинг: Цена: 4592.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this follow-up to the author`s bestselling classic, "The Lady Tasting Tea," David Salsburg takes a fresh and insightful look at the history of statistical development by examing errors, blunders and outright lies in many different models taken from a variety of fields including economics, biology, physics and sports.
Автор: Bollman, Mark (albion College, Albion, Michigan, Usa) Название: Mathematics of keno and lotteries ISBN: 113872372X ISBN-13(EAN): 9781138723726 Издательство: Taylor&Francis Рейтинг: Цена: 9339.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mathematics of Keno and Lotteries is an elementary treatment of the mathematics, primarily probability and simple combinatorics, involved in lotteries and keno. Keno has a long history as a high-advantage, high-payoff casino game, and state lottery games such as Powerball are mathematically similar.
Автор: Kolaczyk Eric D Название: Topics at the Frontier of Statistics and Network Analysis ISBN: 1108407129 ISBN-13(EAN): 9781108407120 Издательство: Cambridge Academ Рейтинг: Цена: 4750.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This snapshot of the current frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design. Primarily for graduate students and researchers in statistics and closely related fields, emphasis is not only on what has been done, but on what remains to be done.
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