Контакты/Проезд  Доставка и Оплата Помощь/Возврат
История
  +7 707 857-29-98
  +7(7172) 65-23-70
  10:00-18:00 пн-пт
  shop@logobook.kz
   
    Поиск книг                        
Найти
  Зарубежные издательства Российские издательства  
Авторы | Каталог книг | Издательства | Новинки | Учебная литература | Акции | Бестселлеры | |
 

Statistical Learning of Complex Data, Francesca Greselin; Laura Deldossi; Luca Bagnato;


Варианты приобретения
Цена: 111790.00T
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: 262 шт.  
При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
При условии наличия книги у поставщика.

Добавить в корзину
в Мои желания

Автор: Francesca Greselin; Laura Deldossi; Luca Bagnato;
Название:  Statistical Learning of Complex Data
ISBN: 9783030211394
Издательство: Springer
Классификация:




ISBN-10: 3030211398
Обложка/Формат: Soft cover
Страницы: 201
Вес: 0.34 кг.
Дата издания: 2019
Серия: Studies in Classification, Data Analysis, and Knowledge Organization
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 18 tables, color; 11 illustrations, color; 26 illustrations, black and white; xiii, 201 p. 37 illus., 11 illus. in color.
Размер: 234 x 156 x 12
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification. It gathers selected and peer-reviewed contributions presented at the 11th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), held in Milan, Italy, on September 13–15, 2017.
Дополнительное описание:
Preface.- Contributors.- Part I Clustering and Classification.- 1.1 Cluster Weighted Beta Regression: a simulation study.- 1.2 Detecting wine adulterations employing robust mixture of Factor Analyzers.- 1.3 Simultaneous supervised and unsupervised


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
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.

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
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.

Topological and Statistical Methods for Complex Data

Автор: Janine Bennett; Fabien Vivodtzev; Valerio Pascucci
Название: Topological and Statistical Methods for Complex Data
ISBN: 3662448998 ISBN-13(EAN): 9783662448991
Издательство: Springer
Рейтинг:
Цена: 130430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013.

Topological and Statistical Methods for Complex Data

Автор: Janine Bennett; Fabien Vivodtzev; Valerio Pascucci
Название: Topological and Statistical Methods for Complex Data
ISBN: 3662513706 ISBN-13(EAN): 9783662513705
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013.

Statistical Modeling and Analysis for Complex Data Problems

Автор: Pierre Duchesne; Bruno R?millard
Название: Statistical Modeling and Analysis for Complex Data Problems
ISBN: 144193751X ISBN-13(EAN): 9781441937513
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors - largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes - present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.


Statistical Modelling of Complex Correlated and Clustered Data Household Surveys in Africa

Автор: Ngianga-Bakwin Kandala
Название: Statistical Modelling of Complex Correlated and Clustered Data Household Surveys in Africa
ISBN: 1536159816 ISBN-13(EAN): 9781536159813
Издательство: Nova Science
Рейтинг:
Цена: 215410.00 T
Наличие на складе: Невозможна поставка.
Описание: In order to assist a hospital in managing its resources and patients, modelling the length of stay is highly important. Recent health scholarship and practice has largely remained empirical, dwelling on primary data. This is critically important, first, because health planners generally rely on data to establish trends and patterns of disease burden at national or regional level. Secondly, epidemiologists depend on data to investigate possible risk factors of the disease. Yet the use of routine or secondary data has, in recent years, proved increasingly significant in such endeavours. Various units within the health systems collected such data primarily as part of the process for surveillance, monitoring and evaluation. Such data is sometimes periodically supplemented by population-based sample survey datasets. Thirdly, coupled with statistical tools, public health professionals are able to analyze health data and breathe life into what may turn out to be meaningless data. The main focus of this book is to present and showcase advanced modelling of routine or secondary survey data. Studies demonstrate that statistical literacy and knowledge are needed to understand health research outputs. The advent of user-friendly statistical packages combined with computing power and widespread availability of public health data resulted in more reported epidemiological studies in literature. However, analysis of secondary data, has some unique challenges. These are most widely reported health literature, so far has failed to recognize resulting in inappropriate analysis, and erroneous conclusions. This book presents the application of advanced statistical techniques to real examples emanating from routine or secondary survey data. These are essentially datasets in which the two editors have been involved, demonstrating how to tackle these challenges. Some of these challenges are: the complex sampling design of the surveys, the hierarchical nature of the data, the dependence of data at the sampled cluster and missing data among many more challenges. Using data from the Health Management Information System (HMIS), and Demographic and Health Survey (DHS), we provide various approaches and techniques of dealing with data complexity, how to handle correlated or clustered data. Each chapter presents an example code, which can be used to analyze similar data in R, Stata or SPSS. To make the book more concise, we have provided the codes on the books website. The book considers four main topics in the field of health sciences research: (i) structural equation modeling; (ii) spatial and spatio-temporal modeling; (iii) correlated or clustered copula modeling; and (iv) survival analysis. The book has potential to impact methodologists, including students undertaking Masters or Doctoral level programmes as well as other researchers seeking some related reference on quantitative analysis in public health or health sciences or other areas where data of similar nature would be applicable. Further the book can be a resource to public health professionals interested in quantitative approaches to answer questions of epidemiological nature. Each chapter starts with a motivating background, review of statistical methods, analysis and results, ending discussion and possible recommendations.

Microhydrodynamics, Brownian Motion, and Complex Fluids

Автор: Michael D. Graham
Название: Microhydrodynamics, Brownian Motion, and Complex Fluids
ISBN: 1107024641 ISBN-13(EAN): 9781107024649
Издательство: Cambridge Academ
Рейтинг:
Цена: 79200.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Flows of complex fluids and other soft materials are ubiquitous in nature and technology, from blood flow to advanced manufacturing. Understanding them requires knowledge from a number of areas. This book brings these topics together in a unique, self-contained and integrated treatment, allowing the reader to see them in context.

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
Рейтинг:
Цена: 78590.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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.


Microhydrodynamics, brownian motion, and complex fluids

Автор: Graham, Michael D. (university Of Wisconsin, Madison)
Название: Microhydrodynamics, brownian motion, and complex fluids
ISBN: 1107695937 ISBN-13(EAN): 9781107695931
Издательство: Cambridge Academ
Рейтинг:
Цена: 40130.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Flows of complex fluids and other soft materials are ubiquitous in nature and technology, from blood flow to advanced manufacturing. Understanding them requires knowledge from a number of areas. This book brings these topics together in a unique, self-contained and integrated treatment, allowing the reader to see them in context.

Statistical Inference for Engineers and Data Scientists

Автор: Moulin Pierre
Название: Statistical Inference for Engineers and Data Scientists
ISBN: 1107185920 ISBN-13(EAN): 9781107185920
Издательство: Cambridge Academ
Рейтинг:
Цена: 67590.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An up-to-date and mathematically accessible introduction to the tools needed to address modern inference problems in engineering and data science. Richly illustrated with examples and exercises connecting the theory with practice, it is the `go to` guide for students studying the topic, and an excellent reference for researchers and practitioners.

Data Science and Machine Learning: Mathematical and Statistical Methods

Автор: Kroese, Dirk P. Botev, Zdravko
Название: Data Science and Machine Learning: Mathematical and Statistical Methods
ISBN: 1138492531 ISBN-13(EAN): 9781138492530
Издательство: Taylor&Francis
Рейтинг:
Цена: 93910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this book is to provide an accessible, yet comprehensive, account of data science and machine learning. It is intended for anyone interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.

Statistical and econometric methods for transportation data analysis

Автор: Washington, Simon Mannering, Fred (university Of S
Название: Statistical and econometric methods for transportation data analysis
ISBN: 0367199025 ISBN-13(EAN): 9780367199029
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Describing tools commonly used in the field, this textbook provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies in various aspects of transportation planning, engineering, safety, and economics.


Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2)
ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
Kaspi QR
   В Контакте     В Контакте Мед  Мобильная версия