Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T 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: 60190.00 T 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: Little Название: Statistical Analysis with Missing Data, Third Edit ion ISBN: 0470526793 ISBN-13(EAN): 9780470526798 Издательство: Wiley Рейтинг: Цена: 84430.00 T 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: Matange Sanjay, Heath Dan, Sas Institute Название: Statistical Graphics Procedures by Example: Effective Graphs Using SAS ISBN: 1607647621 ISBN-13(EAN): 9781607647621 Издательство: Неизвестно Рейтинг: Цена: 85770.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Gould, William Название: The Mata book ISBN: 159718263X ISBN-13(EAN): 9781597182638 Издательство: Taylor&Francis Рейтинг: Цена: 61240.00 T 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: W.J.J. Rey Название: Introduction to Robust and Quasi-Robust Statistical Methods ISBN: 3540128662 ISBN-13(EAN): 9783540128663 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Cameron Название: Microeconometrics Using Stata ISBN: 1597180734 ISBN-13(EAN): 9781597180733 Издательство: Taylor&Francis Рейтинг: Цена: 83690.00 T Наличие на складе: Нет в наличии. 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.
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T 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: Speed Название: Statistical Analysis of Gene Expression Microarray Data ISBN: 1584883278 ISBN-13(EAN): 9781584883272 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Невозможна поставка. Описание: Written by pre-eminent world authorities in the field, this is a reference for the statistical analysis of genetic microarray data. Starting from the first steps of genetic microarray data analysis, this book covers the important topics and common methodologies for analyzing gene expression data.
Автор: Constantino Tsallis Название: Introduction to Nonextensive Statistical Mechanics ISBN: 0387853588 ISBN-13(EAN): 9780387853581 Издательство: Springer Рейтинг: Цена: 78350.00 T 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.
Автор: L D Landau Название: Statistical Physics, ISBN: 0750633727 ISBN-13(EAN): 9780750633727 Издательство: Elsevier Science Рейтинг: Цена: 78590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A lucid presentation of statistical physics and thermodynamics which develops from the general principles to give a large number of applications of the theory.
Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables.
Three examples of such experiments are treated in this book. First, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described.
In this book, asymptotic properties of several sequences of estimators are detailed. The notion of asymptotical efficiency is discussed for the different statistical experiments considered in order to give the proper sense of estimation risk. Eighty examples and computations with R software are given throughout the text.
Examines a range of statistical inference methods in the context of finance and insurance applications
Presents the LAN (local asymptotic normality) property of likelihoods
Combines the proofs of LAN property for different statistical experiments that appears in financial and insurance mathematics
Provides the proper description of such statistical experiments and invites readers to seek optimal estimators (performed in R) for such statistical experiments
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