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Statistical Rethinking, McElreath, Richard


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Цена: 83690.00T
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Автор: McElreath, Richard   (Ричард МакЭлреат)
Название:  Statistical Rethinking
Перевод названия: Ричард МакЭлреат: Статистическое переосмысление
ISBN: 9780367139919
Издательство: Taylor&Francis
Классификация:


ISBN-10: 036713991X
Обложка/Формат: Hardcover
Страницы: 612
Вес: 1.57 кг.
Дата издания: 16.03.2020
Серия: Chapman & Hall/CRC Texts in Statistical Science
Язык: English
Издание: 2 ed
Размер: 256 x 188 x 32
Читательская аудитория: Tertiary education (us: college)
Основная тема: Statistics & Computing
Подзаголовок: A Bayesian Course with Examples in R and STAN
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание: Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.

      Старое издание
Statistical rethinking

Автор: Mcelreath, Richard
Название: Statistical rethinking
ISBN: 1482253445 ISBN-13(EAN): 9781482253443
Издательство: Taylor&Francis
Цена: 81670 T
Наличие на складе: Поставка под заказ.


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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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.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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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.

The Mata book

Автор: Gould, William
Название: The Mata book
ISBN: 159718263X ISBN-13(EAN): 9781597182638
Издательство: Taylor&Francis
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Цена: 61240.00 T
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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.

Microeconometrics Using Stata

Автор: Cameron
Название: Microeconometrics Using Stata
ISBN: 1597180734 ISBN-13(EAN): 9781597180733
Издательство: Taylor&Francis
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Цена: 83690.00 T
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.

Statistical Inference in Finan cial and Insurance Mathematics with R

Автор: Brouste Alexandre
Название: Statistical Inference in Finan cial and Insurance Mathematics with R
ISBN: 1785480839 ISBN-13(EAN): 9781785480836
Издательство: Elsevier Science
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Цена: 150470.00 T
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Описание:

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

Introduction to Probability with Statistical Applications

Автор: Schay G.
Название: Introduction to Probability with Statistical Applications
ISBN: 3319306189 ISBN-13(EAN): 9783319306186
Издательство: Springer
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Цена: 62410.00 T
Наличие на складе: Поставка под заказ.
Описание: Now inits second edition, this textbook serves as an introduction toprobability and statistics for non-mathematics majors who do not need theexhaustive detail and mathematical depth provided in more comprehensivetreatments of the subject. The presentation covers the mathematical laws ofrandom phenomena, including discrete and continuous random variables,expectation and variance, and common probability distributions such as thebinomial, Poisson, and normal distributions. More classical examples such asMontmort's problem, the ballot problem, and Bertrand’s paradox are nowincluded, along with applications such as the Maxwell-Boltzmann andBose-Einstein distributions in physics.Keyfeatures in new edition:* 35 newexercises* Expanded sectionon the algebra of sets *Expanded chapters on probabilities to include more classical examples* Newsection on regression* Onlineinstructors' manual containing solutions to all exercises

Mathematical and Statistical Methods for Actuarial Sciences and Finance

Автор: Marco Corazza; Cira Perna; Marilena Sibillo; Flore
Название: Mathematical and Statistical Methods for Actuarial Sciences and Finance
ISBN: 3319502336 ISBN-13(EAN): 9783319502335
Издательство: Springer
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Цена: 93160.00 T
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Описание: This volume gathers selected peer-reviewed papers presented at the "International MAF Conference 2016 - Mathematical and Statistical Methods for Actuarial Sciences and Finance" held in Paris at the University of Paris-Dauphine from March 30 to April 1, 2016.

Introduction to the Mathematical and Statistical Foundations of Econometrics

Автор: Herman J. Bierens
Название: Introduction to the Mathematical and Statistical Foundations of Econometrics
ISBN: 0521542243 ISBN-13(EAN): 9780521542241
Издательство: Cambridge Academ
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Цена: 44350.00 T
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Описание: Intended for use in a rigorous introductory PhD level course in econometrics, or a field course in econometric theory, this book covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, and more.

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition

Автор: Nicholas J. Horton , Ken Kleinman
Название: Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition
ISBN: 1482237369 ISBN-13(EAN): 9781482237368
Издательство: Taylor&Francis
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Цена: 78590.00 T
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Описание:

Improve Your Analytical Skills

Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.

New to the Second Edition

  • The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
  • New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
  • New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
  • New chapter on simulation that includes examples of data generated from complex models and distributions
  • A detailed discussion of the philosophy and use of the knitr and markdown packages for R
  • New packages that extend the functionality of R and facilitate sophisticated analyses
  • Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots

Easily Find Your Desired Task

Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.


Statistical Analysis with Missing Data, Third Edit ion

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
Рейтинг:
Цена: 84430.00 T
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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.

Statistical Thermodynamics: Basics and Application s to Chemical Systems

Автор: Teraoka
Название: Statistical Thermodynamics: Basics and Application s to Chemical Systems
ISBN: 1118305116 ISBN-13(EAN): 9781118305119
Издательство: Wiley
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Цена: 86540.00 T
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Описание: Written to introduce readers to molecular descriptions of thermodynamics, chemical systems, and biomolecules, Statistical Thermodynamics discusses the aspects of statistical thermodynamics of most use and interest to chemistry students.

Statistical Thinking from Scratch

Автор: Edge M D
Название: Statistical Thinking from Scratch
ISBN: 0198827636 ISBN-13(EAN): 9780198827634
Издательство: Oxford Academ
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Цена: 47510.00 T
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Описание: Focuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.


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