Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: J. Cohen Название: Statistical power analysis for the behavioral sciences ISBN: 0805802835 ISBN-13(EAN): 9780805802832 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This non-technical guide to power analysis in research planning in the behavioural sciences, provides users of applied statistics with the tools needed for more effective analysis. This edition includes a new chapter covering power analysis in set correlations and multivariate methods.
Автор: Zwanzig, Robert (Chief, Section on Theoretical Bio Название: Nonequilibrium Statistical Mechanics ISBN: 0195140184 ISBN-13(EAN): 9780195140187 Издательство: Oxford Academ Рейтинг: Цена: 22176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the main principles and methods of nonequilibrium statistical mechanics, a topic studied by both chemists and physicists. This book is written for graduate students and scientists who already have knowledge of basic equilibrium statistical mechanics and who are interested in the more complex field of time-dependent nonequilibrium statistical mechanics.
Автор: Constantino Tsallis Название: Introduction to Nonextensive Statistical Mechanics ISBN: 0387853588 ISBN-13(EAN): 9780387853581 Издательство: Springer Рейтинг: Цена: 11753.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Metaphors, generalizations and unifications are natural and desirable ingredients of the evolution of scientific theories and concepts. This book focuses on nonextensive statistical mechanics, a generalization of Boltzmann-Gibbs (BG) statistical mechanics, one of the greatest monuments of contemporary physics.
Описание: A concise 2006 introduction to key concepts and tools of statistical mechanics. Self-contained, it combines analytical and numerical techniques, and presents a diverse range of applications. Built on many years` teaching experience, this textbook is ideal for advanced students across the physical sciences.
Автор: Little Название: Statistical Analysis with Missing Data, Third Edit ion ISBN: 0470526793 ISBN-13(EAN): 9780470526798 Издательство: Wiley Рейтинг: Цена: 12664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.
Автор: Gould, William Название: The Mata book ISBN: 159718263X ISBN-13(EAN): 9781597182638 Издательство: Taylor&Francis Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Mata Book: A Book for Serious Programmers and Those Who Want to Be is the book that Stata programmers have been waiting for. Mata is a serious programming language for developing small- and large-scale projects and for adding features to Stata.
Автор: Davey, Adam Savla, Jyoti Название: Statistical power analysis with missing data ISBN: 0805863699 ISBN-13(EAN): 9780805863697 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as:
How missing data affects the statistical power in a study
How much power is likely with different amounts and types of missing data
How to increase the power of a design in the presence of missing data, and
How to identify the most powerful design in the presence of missing data.
Points of Reflection encourage readers to stop and test their understanding of the material. Try Me sections test one's ability to apply the material. Troubleshooting Tips help to prevent commonly encountered problems. Exercises reinforce content and Additional Readings provide sources for delving more deeply into selected topics. Numerous examples demonstrate the book's application to a variety of disciplines. Each issue is accompanied by its potential strengths and shortcomings and examples using a variety of software packages (SAS, SPSS, Stata, LISREL, AMOS, and MPlus). Syntax is provided using a single software program to promote continuity but in each case, parallel syntax using the other packages is presented in appendixes. Routines, data sets, syntax files, and links to student versions of software packages are found at www.psypress.com/davey. The worked examples in Part 2 also provide results from a wider set of estimated models. These tables, and accompanying syntax, can be used to estimate statistical power or required sample size for similar problems under a wide range of conditions.
Class-tested at Temple, Virginia Tech, and Miami University of Ohio, this brief text is an ideal supplement for graduate courses in applied statistics, statistics II, intermediate or advanced statistics, experimental design, structural equation modeling, power analysis, and research methods taught in departments of psychology, human development, education, sociology, nursing, social work, gerontology and other social and health sciences. The book's applied approach will also appeal to researchers in these areas. Sections covering Fundamentals, Applications, and Extensions are designed to take readers from first steps to mastery.
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 22968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.
Автор: Cameron Название: Microeconometrics Using Stata ISBN: 1597180734 ISBN-13(EAN): 9781597180733 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Поставка под заказ.
Описание: Updated to reflect Stata 11, this revised edition offers a complete and up-to-date survey of microeconometric methods available in Stata. The authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11.
The book explores several open questions in the philosophy and the foundations of statistical mechanics. Each chapter is written by a leading expert in philosophy of physics and/or mathematical physics. Here is a list of questions that are addressed in the book:
Boltzmann showed how the phenomenological laws of thermodynamics, such as the second law of thermodynamics, can be suitably derived from statistical mechanics, which is based on classical mechanics. What exactly does this explanation amount to?
Assuming that Boltzmann is able to explain the thermodynamic arrow of time connected with the second law, what about the psychological arrow?
Many physicists use the notion of typicality instead of the one of probability when discussing statistical mechanics. What is typicality? What is its connection with probability? Is typicality explanatory?
How can one extend Boltzmann's analysis to the quantum domain? Can indeterminism help or it does not play a fundamental role?
How does this approach extend to theories in which gravity plays an important role?
Boltzmann's explanation fundamentally involves cosmology: for the explanation to go through the Big Bang needs to have had extremely low entropy. Does the fact that the Big Bang was a low entropy state imply that it was, in some sense, "highly improbable" and requires an explanation? Are there approaches in which one can avoid postulating something like the past hypothesis?
Statistical mechanics has two main formulations: one due to Boltzmann and the other due to Gibbs. What is the connection between the two formulations? Is one more fundamental than the other?
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