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Даже в литературных текстах: романах-приключениях и фантастических рассказах встречаются головоломки, которые без знания математики не разрешить. «Математика в занимательных рассказах» Якова Перельмана поможет читателю понять теорию вероятности, разгадать загадку пирамиды Хеопса и вместе с героями Жюля Верна, Герберта Уэллса и других писателей совершить самые невероятные путешествия – на поверхность мыльного пузыря, на Луну и даже… путешествие во времени! Рассказы и отрывки из романов сопровождаются математическими пояснениями Перельмана и перемежаются числовыми анекдотами, задачами и фокусами с числами. Для среднего школьного возраста.

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В работе предложен новый метод обнаружения одного структурного сдвига в GARCH(1,1) модели, основанный на статистике Колмогорова–Смирнова. Хорошие свойства предлагаемого метода подкрепляются численными экспериментами. Метод сопоставляется с тремя широко известными CUSUM-методами обнаружения структурных сдвигов в GARCH моделях: KL (Kokoszka, Leipus, 1999), IT (Inclán, Tiao, 1994) и LTM (Lee et al., 2004). Для генерации GARCH процессов использовались временные ряды доходностей 26 российских ценных бумаг. На основе проведенных экспериментов показано, что предлагаемый метод обладает высокой конкурентоспособностью и занимает в некотором смысле «компромиссное» положение между KL-методом, имеющим высокие мощность и вероятность ошибки первого рода, и IT- и LTM-методами, мощность и вероятности ошибок первого рода которых низки.

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В данной работе представлены результаты моделирования миграционных процессов выпускников вузов РФ, в том числе с учетом влияния пространственного эффекта соседних регионов. Значимыми факторами миграции выпускников являются более высокий уровень доходов, ВРП на душу населения и уровень безработицы в принимающем регионе. С помощью инструментария пространственной эконометрики доказано наличие положительной пространственной автокорреляции по оттоку и притоку выпускников между соседними регионами.

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‘Brilliant and fascinating. No one is better at making the recondite accessible and exciting’ Bill BrysonBritain’s most famous mathematician takes us to the edge of knowledge to show us what we cannot know.Is the universe infinite?Do we know what happened before the Big Bang?Where is human consciousness located in the brain?And are there more undiscovered particles out there, beyond the Higgs boson?In the modern world, science is king: weekly headlines proclaim the latest scientific breakthroughs and numerous mathematical problems, once indecipherable, have now been solved. But are there limits to what we can discover about our physical universe?In this very personal journey to the edges of knowledge, Marcus du Sautoy investigates how leading experts in fields from quantum physics and cosmology, to sensory perception and neuroscience, have articulated the current lie of the land. In doing so, he travels to the very boundaries of understanding, questioning contradictory stories and consulting cutting edge data.Is it possible that we will one day know everything? Or are there fields of research that will always lie beyond the bounds of human comprehension? And if so, how do we cope with living in a universe where there are things that will forever transcend our understanding?In What We Cannot Know, Marcus du Sautoy leads us on a thought-provoking expedition to the furthest reaches of modern science. Prepare to be taken to the edge of knowledge to find out if there’s anything we truly cannot know.

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This book will tell you how to find and effectively correct missed data in mathematics and how to apply some simple and effective exercises that will considera by save your time and nerves when studying mathematics and preparing for exams.Also it will show in details some other major pitfalls – mathematical skills which were not learned and understood by a huge number of students and this prevents them from getting correct and confident answers when solving mathematical problems and tasks.

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В книге собраны уникальные авторские головоломки на различные темы: логические, физические, геометрические, вероятностные, числовые и пр. Ко всем головоломкам приведены ответы, ко многим – решения. Для всех любителей математики.

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An in-depth description of the state-of-the-art of 3D shape analysis techniques and their applications This book discusses the different topics that come under the title of «3D shape analysis». It covers the theoretical foundations and the major solutions that have been presented in the literature. It also establishes links between solutions proposed by different communities that studied 3D shape, such as mathematics and statistics, medical imaging, computer vision, and computer graphics. The first part of 3D Shape Analysis: Fundamentals, Theory, and Applications provides a review of the background concepts such as methods for the acquisition and representation of 3D geometries, and the fundamentals of geometry and topology. It specifically covers stereo matching, structured light, and intrinsic vs. extrinsic properties of shape. Parts 2 and 3 present a range of mathematical and algorithmic tools (which are used for e.g., global descriptors, keypoint detectors, local feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D objects. Both also place strong emphasis on recent techniques motivated by the spread of commodity devices for 3D acquisition. Part 4 demonstrates the use of these techniques in a selection of 3D shape analysis applications. It covers 3D face recognition, object recognition in 3D scenes, and 3D shape retrieval. It also discusses examples of semantic applications and cross domain 3D retrieval, i.e. how to retrieve 3D models using various types of modalities, e.g. sketches and/or images. The book concludes with a summary of the main ideas and discussions of the future trends. 3D Shape Analysis: Fundamentals, Theory, and Applications is an excellent reference for graduate students, researchers, and professionals in different fields of mathematics, computer science, and engineering. It is also ideal for courses in computer vision and computer graphics, as well as for those seeking 3D industrial/commercial solutions.

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Earthquake occurrence modeling is a rapidly developing research area. This book deals with its critical issues, ranging from theoretical advances to practical applications. The introductory chapter outlines state-of-the-art earthquake modeling approaches based on stochastic models. Chapter 2 presents seismogenesis in association with the evolving stress field. Chapters 3 to 5 present earthquake occurrence modeling by means of hidden (semi-)Markov models and discuss associated characteristic measures and relative estimation aspects. Further comparisons, the most important results and our concluding remarks are provided in Chapters 6 and 7.

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A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators.The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.