Reflections on the Foundations of Probability and Statistics, Augustin

Автор: Thomas A. Garrity
Название: All the Math You Missed
ISBN: 1009009192 ISBN-13(EAN): 9781009009195
Издательство: Cambridge Academ
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Цена: 26400.00 T
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Описание: The second edition of this bestselling book provides an overview of the key topics in undergraduate mathematics, allowing beginning graduate students to fill in any gaps in their knowledge. With numerous examples, exercises and suggestions for further reading, it is a must-have for anyone looking to learn some serious mathematics quickly.

Автор: Jun Otsuka
Название: Thinking About Statistics The Philosophical Foundations
ISBN: 1032333103 ISBN-13(EAN): 9781032333106
Издательство: Taylor&Francis
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Цена: 132710.00 T
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Описание: Simply stated, this book bridges the gap between statistics and philosophy. It does this by delineating the conceptual cores of various statistical methodologies (Bayesian/frequentist statistics, model selection, machine learning, causal inference etc.) and drawing out their philosophical implications.

Автор: David Atkinson; Jeanne Peijnenburg
Название: Fading Foundations
ISBN: 3319863681 ISBN-13(EAN): 9783319863689
Издательство: Springer
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Цена: 46570.00 T
Наличие на складе: Нет в наличии.
Описание: This book is open access under a CC BY 4.0 license.This book addresses the age-old problem of infinite regresses in epistemology. How can we ever come to know something if knowing requires having good reasons, and reasons can only be good if they are backed by good reasons in turn?

Автор: Weatherford, Roy
Название: Philosophical Foundations of Probability Theory
ISBN: 1032308508 ISBN-13(EAN): 9781032308500
Издательство: Taylor&Francis
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Цена: 112290.00 T
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Автор: William E. Schiesser
Название: PDE Models for Atherosclerosis Computer Implementation in R
ISBN: 1681734451 ISBN-13(EAN): 9781681734453
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
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Описание: Atherosclerosis is a pathological condition of the arteries in which plaque buildup and stiffening (hardening) can lead to stroke, myocardial infarction (heart attacks), and even death. Cholesterol in the blood is a key marker for atherosclerosis, with two forms: (1) LDL - low density lipoproteins and (2) HDL - high density lipoproteins. Low LDL and high HDL concentrations are generally considered essential for limited atherosclerosis and good health.This book pertains to a mathematical model for the spatiotemporal distribution of LDL and HDL in the arterial endothelial inner layer (EIL, intima). The model consists of a system of six partial differential equations (PDEs) with the dependent variables1. concentration of modified LDL2. ℎ concentration of HDL3. concentration of chemoattractants4. concentration of ES cytokines5. density of monocytes/macrophages6. density of foam cells and independent variables1. distance from the inner arterial wall2. timeThe focus of this book is a discussion of the methodology for placing the model on modest computers for study of the numerical solutions. The foam cell density as a function of the bloodstream LDL and HDL concentrations is of particular interest as a precursor for arterial plaque formation and stiffening.The numerical algorithm for the solution of the model PDEs is the method of lines (MOL), a general procedure for the computer-based numerical solution of PDEs. The MOL coding (programming) is in R, a quality, open-source scientific computing system that is readily available from the Internet. The R routines for the PDE model are discussed in detail, and are available from a download link so that the reader/analyst/researcher can execute the model to duplicate the solutions reported in the book, then experiment with the model, for example, by changing the parameters (constants) and extending the model with additional equations.

Автор: Gunter Last, Mathew Penrose
Название: Lectures on the Poisson Process
ISBN: 1107088011 ISBN-13(EAN): 9781107088016
Издательство: Cambridge Academ
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Цена: 81310.00 T
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Описание: This self-contained introduction to the Poisson process covers basic theory and certain advanced topics in the setting of a general abstract measure space. The text includes applications and numerous exercises, and is ideal for graduate courses or self-study by mathematicians, physicists, and engineers.

Автор: Samantha Kleinberg
Название: Time and Causality Across the Sciences
ISBN: 1108476678 ISBN-13(EAN): 9781108476676
Издательство: Cambridge Academ
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Цена: 63360.00 T
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Описание: This book provides an entry point for researchers in any field, bringing together perspectives collected from a large body of work on causality across disciplines. Topics include whether quantum mechanics allows causes to precede their effects, the integration of mechanisms, and insight into the role played by intervention and timing information.

Автор: Gut
Название: An Intermediate Course in Probability
ISBN: 1441901612 ISBN-13(EAN): 9781441901613
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book covers the basic results and methods in probability theory. This new edition offers updated content, 100 additional problems for solution, and a new chapter glimpsing further topics such as stable distributions, domains of attraction and martingales.

Автор: Dudin
Название: Information Technologies and Mathematical Modelling. Queueing Theory and Applications
ISBN: 3319975943 ISBN-13(EAN): 9783319975948
Издательство: Springer
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Цена: 46570.00 T
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Описание: The conference covers various aspects of information technologies, focusing on queueing theory, stochastic processes, Markov processes, renewal theory, network performance equation and network protokols.

Автор: Unpingco Jose
Название: Python for Probability, Statistics, and Machine Learning
ISBN: 3030185443 ISBN-13(EAN): 9783030185442
Издательство: Springer
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Цена: 55890.00 T
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Описание: ¢ Are you member of either the management team or the board and do you see the need to adapt your organization to Agile? Do you intend to make the organization more agile? ¢ Are you a coach helping organizations in the transformation to becoming more agile? And are you planning to support this transition using a bottom-up or top-down approach?In this pocket guide you will find a practical approach on how to handle this. Governing an organization in a fast-changing world. And all this although the issues of the day require a lot of your attention and can distract you from the results you want to achieve. The authors consider how to operationalize the organization`s strategic goals and consequently the governance of the entire organization.The authors start from the position of: ¢ Clarifying what has to be achieved in the next quarter in order to achieve the strategic goals. ¢ Introducing a system of short cyclical adjustments, with which you can respond to changing demand from customers or emerging laws and regulations. ¢ Working closely together as management team or board towards the long-term strategic goals and preventing everyone within the organization from following their own goals. ¢ Bringing more focus on the operationalization of the strategy, less `fire-fighting` and greater emphasis on fire prevention. ¢ Getting a clear picture of what prevents your employees from doing their jobs effectively. Will you succeed in removing the barriers holding back your organization? The core message of this pocket guide is application of the FOCUS board. This is a visual approach to management and a strong tool for governing the organization. When this is applied, it will result in collaboration between all layers of the organization, enable short cyclical adjustment and provide a clear focus on achieving the strategic goals.

Автор: Giorgos Michel
Название: Probability & Stochastic Processes: A Friendly Introduction for Electrical & Computer Engineers
ISBN: 1681174529 ISBN-13(EAN): 9781681174525
Издательство: Gazelle Book Services
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Цена: 230210.00 T
Наличие на складе: Невозможна поставка.
Описание: In probability theory, a stochastic process, or often random process, is a collection of random variables representing the evolution of some system of random values over time. This is the probabilistic counterpart to a deterministic process (or deterministic system). Instead of describing a process which can only evolve in one way (as in the case, for example, of solutions of an ordinary differential equation), in a stochastic, or random process, there is some indeterminacy: even if the initial condition is known, there are several directions in which the process may evolve. Classic examples of the stochastic process are guessing the length of a queue at a stated time given the random distribution over time of a number of people or objects entering and leaving the queue and guessing the amount of water in a reservoir based on the random distribution of rainfall and water usage. Stochastic processes were first studied rigorously in the late 19th century to aid in understanding financial markets and Brownian motion. This book covers characterisation, structural properties, inference and control of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests.

Автор: David Forsyth
Название: Probability and Statistics for Computer Science
ISBN: 3319877887 ISBN-13(EAN): 9783319877884
Издательство: Springer
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Цена: 46570.00 T
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Описание: This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features:
•   A treatment of random variables and expectations dealing primarily with the discrete case.
•   A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains.•   A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing.•   A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors.•   A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems.•   A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. •   A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals.Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know.  Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.