Showing 25–48 of 158 results
Regression Models for Categorical Dependent Variables Using Stata, Third Edition shows how to use Stata to fit and interpret regression models for categorical data. The third edition is a complete rewrite of the book. Factor variables and the margins command changed how the effects of variables can be estimated and interpreted. In addition, the authors’ views on interpretation have evolved. The changes to Stata and to the authors’ views inspired the authors to completely rewrite their popular SPost commands to take advantage of the power of the margins command and the flexibility of factor-variable notation.
A culmination of the author’s many years of consulting and teaching, Design and Analysis of Experiments with SAS provides practical guidance on the computer analysis of experimental data. It connects the objectives of research to the type of experimental design required, describes the actual process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results.
Drawing on a variety of application areas, from pharmaceuticals to machinery, the book presents numerous examples of experiments and exercises that enable students to perform their own experiments.
Developed from a course taught to senior undergraduates, this book provides a unified introduction to Fourier analysis and special functions based on the Sturm-Liouville theory in L2. The text’s presentation follows a clear, rigorous mathematical style that is highly readable.
An up-to-date version of the complete, self-contained introduction to matrix analysis theory and practiceProviding accessible and in-depth coverage of the most common matrix methods now used in statistical applications, Matrix Analysis for Statistics, Third Edition features an easy-to-follow theorem/proof format. Featuring smooth transitions between topical coverage, the author carefully justifies the step-by-step process of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; and the distribution of quadratic forms.A
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors’ collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions.T
What could be better than the bestselling Schaum’s Outline series? For students looking for a quick nuts-and-bolts overview, it would have to be Schaum’s Easy Outline series. Every book in this series is a pared-down, simplified, and tightly focused version of its predecessor.
This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits for data and information science and technology. The authors’ approach is accessible to students from almost all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification and computer vision. The presentations enables the basis for numerous approaches to solving hard combinatorial optimization problems through randomization and approximation.
Authors: Wickham, Hadley, Sievert, CarsonBrings the book up-to-date with ggplot2 1.0, including major updates to the theme systemNew scales, stats and geoms added throughoutAdditional practice exercisesA revised introduction that focuses on ggplot() instead of qplot()Updated chapters on data and modeling using tidyr, dplyr and broomThis new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease.
Authors: Madsen, Birger StjernholmAimed at practitionersThe presentation is as non-mathematical as possibleIncludes many examples of the use of statistical functions in spreadsheetsEmploys a realistic sample survey as an exemplar throughout the bookFills a gap in the existing literature on statisticsAbout this TextbookThis book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes.
Planning of actions based on decision theory is a hot topic for many disciplines. Seemingly unlimited computing power, networking, integration and collaboration have meanwhile attracted the attention of fields like Machine Learning, Operations Research, Management Science and Computer Science.
STATISTICS FOR BUSINESS AND ECONOMICS brings together more than twenty-five years of author experience, sound statistical methodology, a proven problem-scenario approach, and meaningful applications to demonstrate how statistical information. Discover how the most trusted approach to statistics today is Simply Powerful with the latest market-leading text from respected authors Anderson/Sweeney/Williams. STATISTICS FOR BUSINESS AND ECONOMICS, 11e introduces sound statistical methodology within a strong applications setting.
Clifford analysis, a branch of mathematics that has been developed since about 1970, has important theoretical value and several applications. In this book, the authors introduce many properties of regular functions and generalized regular functions in real Clifford analysis, as well as harmonic functions in complex Clifford analysis.
Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
Through examples of large complex graphs in realistic networks, research in graph theory has been forging ahead into exciting new directions. Graph theory has emerged as a primary tool for detecting numerous hidden structures in various information networks, including Internet graphs, social networks, biological networks, or, more generally, any graph representing relations in massive data sets. How will we explain from first principles the universal and ubiquitous coherence in the structure of these realistic but complex networks? In order to analyze these large sparse graphs, we use combinatorial, probabilistic, and spectral methods, as well as new and improved tools to analyze these networks.
Form Symmetries and Reduction of Order in Difference Equations presents a new approach to the formulation and analysis of difference equations in which the underlying space is typically an algebraic group. In some problems and applications, an additional algebraic or topological structure is assumed in order to define equations and obtain significant results about them. Reflecting the author’s past research experience, the majority of examples involve equations in finite dimensional Euclidean spaces.
The current volume, Advances in Latent Variable Mixture Models, contains chapters by all of the speakers who participated in the 2006 CILVR conference, providing not just a snapshot of the event, but more importantly chronicling the state of the art in latent variable mixture model research. The volume starts with an overview chapter by the CILVR conference keynote speaker, Bengt Muthén, offering a "lay of the land" for latent variable mixture models before the volume moves to more specific constellations of topics.
Introduction to Statistics and SPSS in Psychology guides the reader carefully and concisely up the statistics staircase to success. Each step is supported by helpful visuals as well as advice on how to overcome problems. Interactive, lively, but never patronising, this is the complete guide to statistics that will take readers through their degree course from beginning to end.Take a step in the right direction and tackle statistics head on with this visual introduction.
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methodsFeaturing a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up–to–date coverage of the unique challenges presented in the field of data analysis.T
This manual contains solutions to all exercises from the textbook Vector Calculus by Miroslav Lovric, published by John Wiley & Sons.In most cases, all details of a solution are given. Occasionally, a related theoretical concept, a method or a formula are recalled in order to make the exposition clearer. Details of evaluation of definite integrals are sometimes skipped and the reader is referred to a table of integrals or advised to use a numeric method or appropriate software. (The objective of this course is not to master a dozen integration techniques but rather to understand what the integral involved is all about.)
Authors: Barbeau, Edward J.Includes problems that are prime for standard assignments and more advanced problems for eager studentsProvides a model for institutions who may wish to establish math competitionsPrepares students for the Putnam mathematics competitionsAbout this TextbookThis text records the problems given for the first 15 annual undergraduate mathematics competitions, held in March each year since 2001 at the University of Toronto. Problems cover areas of single-variable differential and integral calculus, linear algebra, advanced algebra, analytic geometry, combinatorics, basic group theory, and number theory.
Consulting and collecting numbers has been a feature of human affairs since antiquity-from the pyramids to tax collection to head counts for military service-but not until the Scientific Revolution in the seventeenth century did social numbers such as births, deaths and marriages begin to be analysed. The Triumph of Numbers explores how numbers have come to assume a leading role in science, in the operations and structure of government, in the analysis of society, in marketing and in many other aspects of daily life.
These lecture notes provide a self-contained introduction to regularity theory for elliptic equations and systems in divergence form. After a short review of some classical results on everywhere regularity for scalar-valued weak solutions, the presentation focuses on vector-valued weak solutions to a system of several coupled equations. In the vectorial case, weak solutions may have discontinuities and so are expected, in general, to be regular only outside of a set of measure zero. Several methods are presented concerning the proof of such partial regularity results, and optimal regularity is discussed.
Karl Gustafson is the creator of the theory of antieigenvalue analysis. Its applications spread through fields as diverse as numerical analysis, wavelets, statistics, quantum mechanics, and finance. Antieigenvalue analysis, with its operator trigonometry, is a unifying language which enables new and deeper geometrical understanding of essentially every result in operator theory and matrix theory, together with their applications. This book will open up its methods to a wide range of specialists.
The general properties and mathematical structures of semiseparable matrices were presented in volume 1 of Matrix Computations and Semiseparable Matrices. In volume 2, Raf Vandebril, Marc Van Barel, and Nicola Mastronardi discuss the theory of structured eigenvalue and singular value computations for semiseparable matrices. These matrices have hidden properties that allow the development of efficient methods and algorithms to accurately compute the matrix eigenvalues.This thorough analysis of semiseparable matrices explains their theoretical underpinnings and contains a wealth of information on implementing them in practice.
Showing 25–48 of 158 results