Statistical Learning and Modeling in Data Analysis: Methods and Applications, Balzano Simona, Porzio Giovanni C., Salvatore Renato
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.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.
This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.
Includes input by practitioners for practitioners
Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
Contains practical advice from successful real-world implementations
Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Описание: Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models--equations of various sorts capturing relationships between variables involved in a complex situation--are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning.This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate ``liberal arts mathematics''-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the ${\tt R}$ statistical package.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Hayes, Monson H. Название: Statistical digital signal processing and modeling ISBN: 0471594318 ISBN-13(EAN): 9780471594314 Издательство: Wiley Рейтинг: Цена: 45636.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book responds to the dramatic growth in digital signal processing (DSP) over the past decade. While its focal point is signal modeling, the book integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectral estimation, and adaptive filtering.
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen
Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically.
This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing.
The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems.
Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Автор: Ramesh S.V. Teegavarapu, Jose D. Salas, Jery R. Stedinger Название: Statistical Analysis of Hydrologic Variables: Methods and Applications ISBN: 078441517X ISBN-13(EAN): 9780784415177 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32294.00 р. Наличие на складе: Нет в наличии.
Описание: Provides a compilation of state-of-the-art statistical methods for analysing and describing critical variables that are part of the hydrological cycle. This resource will assist practicing hydrologists, water resource specialists, researchers, and individuals interested in applications of probabilistic methods in hydrology and water resources.
Автор: Ponnadurai Ramasami Название: Computational Chemistry Methods: Applications ISBN: 3110629925 ISBN-13(EAN): 9783110629927 Издательство: Walter de Gruyter Рейтинг: Цена: 24165.00 р. Наличие на складе: Нет в наличии.
Описание:
This book reviews a variety of methods in computational chemistry and their applications in different fields of current research. Ab initio methods and regression analyses are discussed with special focus on their application to investigate chemical structures as for example dyes or drug compounds. Further topics are the use of computational methods in the modeling of spectroscopic data or to study reaction mechanisms.
Описание: A thorough treatment of the statistical methods used to analyze doubly truncated data
In The Statistical Analysis of Doubly Truncated Data, an expert team of statisticians delivers an up-to-date review of existing methods used to deal with randomly truncated data, with a focus on the challenging problem of random double truncation. The authors comprehensively introduce doubly truncated data before moving on to discussions of the latest developments in the field.
The book offers readers examples with R code along with real data from astronomy, engineering, and the biomedical sciences to illustrate and highlight the methods described within. Linear regression models for doubly truncated responses are provided and the influence of the bandwidth in the performance of kernel-type estimators, as well as guidelines for the selection of the smoothing parameter, are explored.
Fully nonparametric and semiparametric estimators are explored and illustrated with real data. R code for reproducing the data examples is also provided. The book also offers:
A thorough introduction to the existing methods that deal with randomly truncated data
Comprehensive explorations of linear regression models for doubly truncated responses
Practical discussions of the influence of bandwidth in the performance of kernel-type estimators and guidelines for the selection of the smoothing parameter
In-depth examinations of nonparametric and semiparametric estimators
Perfect for statistical professionals with some background in mathematical statistics, biostatisticians, and mathematicians with an interest in survival analysis and epidemiology, The Statistical Analysis of Doubly Truncated Data is also an invaluable addition to the libraries of biomedical scientists and practitioners, as well as postgraduate students studying survival 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: 17609.00 р. 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.
Автор: Ponnadurai Ramasami Название: Computational Chemistry Methods: Applications ISBN: 3110629062 ISBN-13(EAN): 9783110629064 Издательство: Walter de Gruyter Цена: 24165.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book reviews a variety of methods in computational chemistry and their applications in different fields of current research. Ab initio methods and regression analyses are discussed with special focus on their application to investigate chemical structures as for example dyes or drug compounds. Further topics are the use of computational methods in the modeling of spectroscopic data or to study reaction mechanisms.
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