Linear models with r, Faraway, Julian J. (university Of Bath, Uk)
Старое издание
Автор: Faraway Julian J Название: Linear models with R ISBN: 1439887330 ISBN-13(EAN): 9781439887332 Издательство: Taylor&Francis Цена: 13779.00 р. Наличие на складе: Поставка под заказ. Описание:
A Hands-On Way to Learning Data Analysis
Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.
New to the Second Edition
Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality
Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates
Extensive use of the ggplot2 graphics package in addition to base graphics
Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.
Автор: Bergeron Mitchel Название: The Harley-Davidson Source Book: All the Production Models Since 1903 ISBN: 0760361908 ISBN-13(EAN): 9780760361900 Издательство: Quarto Рейтинг: Цена: 5082.00 р. Наличие на складе: Есть (1 шт.) Описание: The Harley-Davidson Source Book celebrates these iconic motorcycles in encyclopedia form. Rich with vivid photography, insightful commentary, and production specs and data, this is the #1 resource for die-hard Harley fans all around the world. When most people close their eyes and imagine a motorcycle, that motorcycle looks very much like a Harley-Davidson. That's because Harley builds the archetypal motorcycle, the mythic bike that exists beyond the input provided by our traditional senses. This is what the philosopher Kant called a priori knowledge, knowledge we can't learn but only intuit. That makes a Harley-Davidson the a priori motorcycle. The Harley-Davidson Motor Co. builds motorcycles that look the way the primordial biker inside each of us feels a motorcycle should be built. This is why Harley-Davidson defines the very word motorcycle for so many people. In The Harley-Davidson Source Book, acclaimed Harley-Davidson historian Mitchel Bergeron covers every motorcycle the company has built, from the very first prototype to the Silent Gray Fellow to the latest CVO Electra Glides and Softails. They're all here--the Knucklehead, the Panhead, the Pea Shooter, the KR, the Sportster, the XR750, the Shovelhead, the Evolution, the Twin Cam, the V-Rod, and all the rest. An authoritative text by noted Harley-Davidson historian and journalist Mitchel Bergeron complemented by modern and period photography and archival marketing materials make this Harley reference complete. The Harley-Davidson Source Book showcases the most storied, celebrated, and downright wild motorcycles ever produced by the Motor Company. This is the ultimate encyclopedia of the ultimate motorcycle.
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 9978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Описание: Now in a thoroughly revised 5th Edition, An Introduction to the Policy Process provides students at all levels with an accessible, readable, and affordable introduction to the field of public policy. In keeping with prior editions, author Tom Birkland conveys the best current thinking on the policy process in a clear, conversational style. Designed to address new developments in both policy theory and policy making, the 5th Edition includes examinations of: the Brexit referendum result and its effects on the UK, EU and world politics, as well as the 2016 election of Donald Trump as President of the United States, and the ways in which these events have caused voters and policy makers to rethink their assumptions; changes to the media environment, including the decline of newspapers and television news, the growth of social media, and the emergence of ‘fake news'; new policy theory developments like the emergence of the Narrative Policy Framework (NPF) and continued and newer applications of existing theories of policy process like Advocacy Coalitions, Multiple Streams, Punctuated Equilibrium, and Institutional Analysis and Development; all-new 'What Does the Research Say?' boxes to illustrate concepts outlined in the book, demonstrate the ways in which the material is applicable to a range of policy problems, and encourage students to further study the policy process and substantive policy matters in which they are interested; and all-new and updated chapter ‘at a glance’ outlines, definitions of key terms, provocative review questions, recommended reading, visual aids and case studies, theoretical literature, and PowerPoint slides and Test Banks to make teaching from the book easier than ever. Firmly grounded in both social science and political science, An Introduction to the Policy Process provides the most up-to-date and thorough overview of the theory and practice of the policy process, ideal for upper-level undergraduate and introductory graduate courses in Public Policy, Public Administration, and Political Science programs.
Автор: Shreve, Steven E. Название: Stochastic Calculus for Finance II ISBN: 0387401016 ISBN-13(EAN): 9780387401010 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "A wonderful display of the use of mathematical probability to derive a large set of results from a small set of assumptions.
Автор: Saenz, Benjamin Alire Название: Inexplicable logic of my life ISBN: 1471171035 ISBN-13(EAN): 9781471171031 Издательство: Simon&Schuster UK Рейтинг: Цена: 1483.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A warmly humane look at universal questions of belonging, infused with humour, from the bestselling author of Aristotle and Dante Discover the Secrets of the Universe
Автор: Strang Название: Differential Equations and Linear Algebra ISBN: 0980232791 ISBN-13(EAN): 9780980232790 Издательство: Cambridge Academ Рейтинг: Цена: 9027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Differential equations and linear algebra are two central topics in the undergraduate mathematics curriculum. This innovative textbook allows the two subjects to be developed either separately or together, illuminating the connections between two fundamental topics, and giving increased flexibility to instructors. It can be used either as a semester-long course in differential equations, or as a one-year course in differential equations, linear algebra, and applications. Beginning with the basics of differential equations, it covers first and second order equations, graphical and numerical methods, and matrix equations. The book goes on to present the fundamentals of vector spaces, followed by eigenvalues and eigenvectors, positive definiteness, integral transform methods and applications to PDEs. The exposition illuminates the natural correspondence between solution methods for systems of equations in discrete and continuous settings. The topics draw on the physical sciences, engineering and economics, reflecting the author's distinguished career as an applied mathematician and expositor.
Автор: Richard J Boucherie, Aleida Braaksma, Henk Tijms Название: Operations Research: Introduction to Models and Methods ISBN: 9811239819 ISBN-13(EAN): 9789811239816 Издательство: World Scientific Publishing Рейтинг: Цена: 8712.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.
The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.
The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.
Each chapter contains numerous exercises, and a large selection of exercises includes solutions.
Автор: Bruce D. Craven; Sardar M. N. Islam Название: Optimization in Economics and Finance ISBN: 1441937145 ISBN-13(EAN): 9781441937148 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
Описание: This book introduces optimal control methods, formulated as optimization problems, applied to business dynamics problems. Business dynamics refers to a combination of business management and financial objectives embedded in a dynamical system model. The model is subject to a control that optimizes a performance index and takes both management and financial aspects into account.Business Dynamics Models: Optimization-Based One Step Ahead Optimal Control includes solutions that provide a rationale for the use of optimal control and guidelines for further investigation into more complex models, as well as formulations that can also be used in a so-called flight simulator mode to investigate different complex scenarios. The text offers a modern programming environment (Jupyter notebooks in JuMP/Julia) for modeling, simulation, and optimization, and Julia code and notebooks are provided on a website for readers to experiment with their own examples.This book is intended for students majoring in applied mathematics, business, and engineering. The authors use a formulation-algorithm-example approach, rather than the classical definition-theorem-proof, making the material understandable to senior undergraduates and beginning graduates.
Автор: Erik W. Grafarend , Silvelyn Zwanzig , Joseph L. Awange Название: Applications of Linear and Nonlinear Models ISBN: 3030945979 ISBN-13(EAN): 9783030945978 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view and a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss–Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters, we concentrate on underdetermined and overdetermined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE, and total least squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimation by the so-called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann–Plucker coordinates, criterion matrices of type Taylor–Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overjet. This second edition adds three new chapters: (1) Chapter on integer least squares that covers (i) model for positioning as a mixed integer linear model which includes integer parameters. (ii) The general integer least squares problem is formulated, and the optimality of the least squares solution is shown. (iii) The relation to the closest vector problem is considered, and the notion of reduced lattice basis is introduced. (iv) The famous LLL algorithm for generating a Lovasz reduced basis is explained. (2) Bayes methods that covers (i) general principle of Bayesian modeling. Explain the notion of prior distribution and posterior distribution. Choose the pragmatic approach for exploring the advantages of iterative Bayesian calculations and hierarchical modeling. (ii) Present the Bayes methods for linear models with normal distributed errors, including noninformative priors, conjugate priors, normal gamma distributions and (iii) short outview to modern application of Bayesian modeling. Useful in case of nonlinear models or linear models with no normal distribution: Monte Carlo (MC), Markov chain Monte Carlo (MCMC), approximative Bayesian computation (ABC) methods. (3) Error-in-variables models, which cover: (i) Introduce the error-in-variables (EIV) model, discuss the difference to least squares estimators (LSE), (ii) calculate the total least squares (TLS) estimator. Summarize the properties of TLS, (iii) explain the idea of simulation extrapolation (SIMEX) estimators, (iv) introduce the symmetrized SIMEX (SYMEX) estimator and its relation to TLS, and (v) short outview to nonlinear EIV models. The chapter on algebraic solution of nonlinear system of equations has also been updated in line with the new emerging field of hybrid numeric-symbolic solutions to systems of nonlinear equations, ermined system of nonlinear equations on curved manifolds. The von Mises–Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter is devoted to probabilistic regression, the special Gauss–Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra, and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger algorithm, especially the C. F. Gauss combinatorial algorithm.
Автор: Nachtsheim;Neter;Kutner Название: Applied Linear Statistical Models with Student CD ISBN: 0071122214 ISBN-13(EAN): 9780071122214 Издательство: McGraw-Hill Рейтинг: Цена: 9265.00 р. Наличие на складе: Поставка под заказ.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
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