Fundamentals of mathematical statistics, Lauritzen, Steffen

Автор: Krickeberg Klaus, Van Trong Pham, Thi My Hanh Pham
Название: Epidemiology: Key to Public Health. 2 ed.
ISBN: 3030163679 ISBN-13(EAN): 9783030163679
Издательство: Springer
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Цена: 93160.00 T
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Описание: ?This unique textbook presents the field of modern epidemiology as a whole; it does not restrict itself to particular aspects. It stresses the fundamental ideas and their role in any situation of epidemiologic practice. Its structure is largely determined by didactic viewpoints.Epidemiology is the art of defining and investigating the influence of factors on the health of populations. Hence the book starts by sketching the role of epidemiology in public health. It then treats the epidemiology of many particular diseases; mathematical modelling of epidemics and immunity; health information systems; statistical methods and sample surveys; clinical epidemiology including clinical trials; nutritional, environmental, social, and genetic epidemiology; and the habitual tools of epidemiologic studies. The book also reexamines the basic difference between the epidemiology of infectious diseases and that of non-infectious ones.The organization of the topics by didactic aspects makes the book ideal for teaching. All examples and case studies are situated in a single country, namely Vietnam; this provides a particularly vivid picture of the role of epidemiology in shaping the health of a population. It can easily be adapted to other developing or transitioning countries.This volume is well suited for courses on epidemiology and public health at the upper undergraduate and graduate levels, while its specific examples make it appropriate for those who teach these fields in developing or emerging countries. New to this edition, in addition to minor revisions of almost all chapters:• Updated data about infectious and non-infectious diseases• An expanded discussion of genetic epidemiology• A new chapter, based on recent research of the authors, on how to build a coherent system of Public Health by using the insights provided by this volume.

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: 76850.00 T
Наличие на складе: Заказано в издательстве.
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: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 33790.00 T
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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: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 52790.00 T
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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: Wackerly, Dennis Mendenhall, William Scheaffer, Ri
Название: Mathematical statistics with applications
ISBN: 0495385069 ISBN-13(EAN): 9780495385066
Издательство: Cengage Learning
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Цена: 62290.00 T
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Описание: Prepare for exams and succeed in your mathematics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in MATHEMATICAL STATISTICS WITH APPLICATIONS, 7th Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.

Автор: Spokoiny Vladimir, Dickhaus Thorsten
Название: Basics of moderm mathematical Statistics
ISBN: 366251348X ISBN-13(EAN): 9783662513484
Издательство: Springer
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Цена: 52170.00 T
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Описание: The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics.

Автор: Lawrence M. Friedman; Curt D. Furberg; David L. De
Название: Fundamentals of Clinical Trials
ISBN: 3319307738 ISBN-13(EAN): 9783319307732
Издательство: Springer
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Цена: 46570.00 T
Наличие на складе: Поставка под заказ.
Описание: This is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials. The three authors of the first four editions have been joined by two others who add great expertise. A chapter on regulatory issues has been included and the chapter on data monitoring has been split into two and expanded. Many contemporary clinical trial examples have been added. There is much new material on adverse events, adherence, issues in analysis, electronic data, data sharing and international trials. This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials to illustrate the fundamentals. The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan and reporting the trial results according to the pre-specified objectives. Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful.

Автор: Hung T. Nguyen; Gerald S. Rogers
Название: Fundamentals of Mathematical Statistics
ISBN: 146138916X ISBN-13(EAN): 9781461389163
Издательство: Springer
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Цена: 74490.00 T
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Описание: This is a text (divided into two volumes) for a two semester course in Mathematical Statistics at the Senior/Graduate level. Volume II: Statistical Inference is designed for the second semester and contains a rigorous introduction to Mathematical Statistics, from random samples to asymptotic theory of statistical inference.

Автор: Hung T. Nguyen; Gerald S. Rogers
Название: Fundamentals of Mathematical Statistics
ISBN: 0387970142 ISBN-13(EAN): 9780387970141
Издательство: Springer
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Цена: 79150.00 T
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Описание: This is the first half of a text for a two semester course in mathematical statistics at the senior/graduate level for those who need a strong background in statistics as an essential tool in their career. To study this text, the reader needs a thorough familiarity with calculus including such things as Jacobians and series but somewhat less intense familiarity with matrices including quadratic forms and eigenvalues. For convenience, these lecture notes were divided into two parts: Volume I, Probability for Statistics, for the first semester, and Volume II, Statistical Inference, for the second. We suggest that the following distinguish this text from other introductions to mathematical statistics. 1. The most obvious thing is the layout. We have designed each lesson for the (U.S.) 50 minute class; those who study independently probably need the traditional three hours for each lesson. Since we have more than (the U.S. again) 90 lessons, some choices have to be made. In the table of contents, we have used a * to designate those lessons which are "interesting but not essential" (INE) and may be omitted from a general course; some exercises and proofs in other lessons are also "INE". We have made lessons of some material which other writers might stuff into appendices. Incorporating this freedom of choice has led to some redundancy, mostly in definitions, which may be beneficial.

Автор: Sivan Toledo
Название: Location Estimation from the Ground Up
ISBN: 1611976286 ISBN-13(EAN): 9781611976281
Издательство: Mare Nostrum (Eurospan)
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Цена: 58100.00 T
Наличие на складе: Нет в наличии.
Описание: The location of an object can often be determined from indirect measurements using a process called estimation. This book explains the mathematical formulation of location-estimation problems and the statistical properties of these mathematical models. It also presents algorithms that are used to resolve these models to obtain location estimates, including the simplest linear models, nonlinear models (location estimation using satellite navigation systems and estimation of the signal arrival time from those satellites), dynamical systems (estimation of an entire path taken by a vehicle), and models with integer ambiguities (GPS location estimation that is centimeter-level accurate).Location Estimation from the Ground Up clearly presents analytic and algorithmic topics not covered in other books, including simple algorithms for Kalman filtering and smoothing, the solution of separable nonlinear optimization problems, estimation with integer ambiguities, and the implicit-function approach to estimating covariance matrices when the estimator is a minimizer or maximizer. It takes a unified approach to estimation while highlighting the differences between classes of estimation problems. The only book on estimation written for math and computer science students and graduates, it includes problems at the end of each chapter, many with solutions, to help readers deepen their understanding of the material and guide them through small programming projects that apply theory and algorithms to the solution of real-world location-estimation problems.The book’s core audience consists of engineers, including software engineers and algorithm developers, and graduate students who work on location-estimation projects and who need help translating the theory into algorithms, code, and deep understanding of the problem in front of them. Instructors in mathematics, computer science, and engineering may also find the book of interest as a primary or supplementary text for courses in location estimation and navigation.

Автор: Darwiche
Название: Modeling and Reasoning with Bayesian Networks
ISBN: 1107678420 ISBN-13(EAN): 9781107678422
Издательство: Cambridge Academ
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Цена: 65470.00 T
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Описание: This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis.

Автор: Donald B. Percival, Andrew T. Walden
Название: Spectral Analysis for Univariate Time Series
ISBN: 1107028140 ISBN-13(EAN): 9781107028142
Издательство: Cambridge Academ
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Цена: 97150.00 T
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Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.