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Applied Reliability Engineering and Risk Analysis - Probabilistic Models and Statistical Inference, Frenkel


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Цена: 20584.00р.
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Автор: Frenkel
Название:  Applied Reliability Engineering and Risk Analysis - Probabilistic Models and Statistical Inference
ISBN: 9781118539422
Издательство: Wiley
Классификация:


ISBN-10: 1118539427
Обложка/Формат: Hardback
Страницы: 448
Вес: 0.86 кг.
Дата издания: 2013
Серия: Quality and reliability engineering series
Язык: English
Размер: 251 x 170 x 26
Читательская аудитория: Professional & vocational
Основная тема: Quality & Reliability
Подзаголовок: Probabilistic models and statistical inference
Ссылка на Издательство: Link
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Поставляется из: Англии


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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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.

Probabilistic Foundations of Statistical Network Analysis

Автор: Crane
Название: Probabilistic Foundations of Statistical Network Analysis
ISBN: 1138585998 ISBN-13(EAN): 9781138585997
Издательство: Taylor&Francis
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Цена: 21437.00 р.
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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. ? ? ? ? ? ?

Mathematical foundations of infinite-dimensional statistical models

Автор: Gine, Evarist Nickl, Richard (university Of Cambridge)
Название: Mathematical foundations of infinite-dimensional statistical models
ISBN: 110899413X ISBN-13(EAN): 9781108994132
Издательство: Cambridge Academ
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Цена: 7286.00 р.
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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 or from Gaussian regression/signal in white noise problems.

Statistical Models and Methods for Reliability and  Survival Analysis

Автор: Couallier
Название: Statistical Models and Methods for Reliability and Survival Analysis
ISBN: 184821619X ISBN-13(EAN): 9781848216198
Издательство: Wiley
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Цена: 25811.00 р.
Наличие на складе: Поставка под заказ.

Statistical Analysis of Reliability and Life-Testing Models

Автор: Bain, Lee
Название: Statistical Analysis of Reliability and Life-Testing Models
ISBN: 0824785061 ISBN-13(EAN): 9780824785062
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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System Reliability Theory: Models, Statistical Methods, and Applications, 2nd Edition

Автор: Marvin Rausand
Название: System Reliability Theory: Models, Statistical Methods, and Applications, 2nd Edition
ISBN: 047147133X ISBN-13(EAN): 9780471471332
Издательство: Wiley
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Цена: 24394.00 р.
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Описание: An examination of system reliability theory, this title features in-depth discussion of dependability management and reliability centered systems as well as functional safety issues-matters critical to the IEC standards.

Modelling, Inference and Data Analysis

Автор: Mavrakakis
Название: Modelling, Inference and Data Analysis
ISBN: 158488939X ISBN-13(EAN): 9781584889397
Издательство: Taylor&Francis
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Цена: 21437.00 р.
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Описание: Covers aspects of probability, distribution theory and random processes that are fundamental to a proper understanding of inference. This book discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models.

Risk Management Technologies

Автор: E.D. Solozhentsev
Название: Risk Management Technologies
ISBN: 9400798776 ISBN-13(EAN): 9789400798779
Издательство: Springer
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Цена: 20516.00 р.
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Описание: This book presents intellectual innovative information (I3) technologies based on logical and probabilistic (LP) risk models covering a range of systems and settings. Offers numerous applications demonstrating the effectiveness of risk management technologies.

Discrete Stochastic Models and Applications for Reliability Engineering and Statistical Quality Control

Автор: Serkan Eryilmaz
Название: Discrete Stochastic Models and Applications for Reliability Engineering and Statistical Quality Control
ISBN: 0367749831 ISBN-13(EAN): 9780367749835
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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Описание: This book provides real-life examples and illustrations of models in reliability engineering and statistical quality control and establishes a connection between the theoretical framework and their engineering applications.

Statistical hypothesis testing in context

Автор: Fay, Michael P. Brittain, Erica H.
Название: Statistical hypothesis testing in context
ISBN: 1108423566 ISBN-13(EAN): 9781108423564
Издательство: Cambridge Academ
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Цена: 7918.00 р.
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Описание: With over 60 years of applied experience, Fay and Brittain present hypothesis testing and compatible confidence intervals, emphasize strategies to address the reproducibility crisis, and provide methods for proper causal interpretation in scientific research. The book presents a full scope of tools and advice on their appropriate use in practice.

Confidence, Likelihood, Probability

Автор: Schweder
Название: Confidence, Likelihood, Probability
ISBN: 0521861608 ISBN-13(EAN): 9780521861601
Издательство: Cambridge Academ
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Цена: 12514.00 р.
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Описание: This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.

Fundamentals of Nonparametric Bayesian Inference

Автор: Ghosal, Subhashis.
Название: Fundamentals of Nonparametric Bayesian Inference
ISBN: 0521878268 ISBN-13(EAN): 9780521878265
Издательство: Cambridge Academ
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Цена: 12989.00 р.
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Описание: Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.


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